- Email: [email protected]
Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like-seeking on Instagram in emerging adulthood
Computers in Human Behavior 71 (2017) 1e10
Contents lists available at ScienceDirect
Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
Full length article
Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like-seeking on Instagram in emerging adulthood Tara M. Dumas a, *, Matthew Maxwell-Smith b, Jordan P. Davis c, Paul A. Giulietti a a b c
Huron University College at Western University, London, Ontario, Canada Western University, London, Ontario, Canada University of Illinois at Urbana-Champaign, Champaign, IL, United States
a r t i c l e i n f o
a b s t r a c t
Article history: Received 16 September 2016 Received in revised form 19 January 2017 Accepted 20 January 2017 Available online 24 January 2017
We examined the extent to which emerging adults engage in different behaviors on Instagram, a popular social networking site, to gain attention and validation from others via “likes.” We also examined individual differences in the frequency of like-seeking behavior and motives for Instagram use as mediators of these relationships. Participants (N ¼ 198 and 265 (replication study)) were recruited via an online crowdsourcing portal to complete a survey. Results demonstrated that, as predicted, participants engaged in an assortment of different like-seeking behaviors. Further, a twofactor solution emerged, with like-seeking behavior separated by whether they were normative (i.e., common or accepted, e.g., using filters or hashtags) or deceptive (e.g., buying likes or changing one’s appearance in photos using software). Deceptive like-seeking was predicted by stronger narcissism and a weaker sense of peer belonging, whereas normative like-seeking was predicted by stronger narcissism and a stronger sense of peer belonging. Further, consistent with hypotheses, significant mediators of the relation between narcissism and deceptive like-seeking included motives to use Instagram to increase popularity and showcase creativity. Results help to identify young people who are more susceptible to engaging in deceptive, potentially harmful acts to gain attention and validation on Instagram. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Instagram Narcissism Peer belonging Loneliness Deception Social networks
1. Introduction Instagram is a photo and video sharing site used via mobile devices that was launched in 2010. At present, Instagram has over 500 million active monthly users, 300 million daily users, and over 95 million photos and videos are posted to Instagram per day (www.instagram.com/press/). The most common age group on Instagram are young people between the ages of 18e29 years of age, or emerging adults, who represent over one third of Instagram users (Duggan & Smith, 2014). Young people in this age group use Instagram more than any other SNS and rate Instagram as being more fun and entertaining than Facebook or Twitter (Pittman, 2015).
* Corresponding author. Huron University College, 1349 Western Road, London, Ontario, N6G 1H3, Canada. E-mail address: [email protected] (T.M. Dumas). http://dx.doi.org/10.1016/j.chb.2017.01.037 0747-5632/© 2017 Elsevier Ltd. All rights reserved.
Researchers have suggested that, as opposed to other SNS sites, Instagram use is focused more on self-presentation and promotion rather than building and maintaining relationships. Almost 25% of the photos on Instagram are focused solely on self-presentation, in the form of “selfies” (i.e., self-portraits taken by the user; Hu, Manikonda, & Kambhampati, 2014). Further, Sheldon and Bryant (2016) identified that, in addition to using Instagram to monitor other individuals (friends and otherwise), university students use Instagram primarily for self-presentation and promotion motives, including documenting their lives to others, expressing and showcasing their creativity, and increasing their popularity among peers. In this paper, we focus on the predictors of emerging adults’ engagement in like-seeking behavior on Instagram, or the extent to which they engage in behaviors to increase the number of individuals who will click a button to indicate that they “like” their photos or videos. Anecdotal evidence suggests that emerging adults engage in a variety of like-seeking behaviors, from uploading
2
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
photos at a specific time of day, to modifying their photos to make them look more attractive, to even purchasing likes or Instagram followers from secondary source sites, although no empirical research has examined the frequency and range of such behaviors. Further, no research has examined psychosocial predictors of these behaviors. Such research is important to identify which young people are most likely to seek personal validation and attention from online sources. In the current project, we examined the following questions that have not been addressed in previous research: (1) How common are different types of like-seeking behaviors among young people? (2) Are there individuals with certain peer relationships, personality traits or psychological adjustment that are more or less likely to engage in these different types of like-seeking activities on Instagram? Finally, (3) what motives explain these likeseeking behaviors? 1.1. Self-promotion and validation-seeking on instagram While the functions of Instagram overlap somewhat with other SNSs like Facebook, Instagram also differs in interesting ways. Primarily, on Facebook, the user can utilize a number of different functions (e.g., chat publicly or privately with friends, join groups, create pages for businesses or hobbies). In contrast, the primary activity on Instagram is to share photos and short videos, or to engage in visual self-presentation of one’s actual or ideal self (Hu et al., 2014), as well as viewing content from others. Because of this, Instagram has several features that help people to modify and distribute their visual content to a larger audience. The site allows users to modify their photos using different filters, so they have more control over the final image. Further, users can add hashtags (#) to their photos or videos, which allow other people to more easily find and view them, regardless of whether these people are mutual friends or “followers.” Consistent with Instagram being an outlet for self-expression, presentation, and impression management, it follows that young people on Instagram are particularly focused on validation or attention through the form of “likes.” Users may upload pictures to Instagram for the purpose of gaining likes, and use Instagram’s built in features to increase the likelihood of receiving likes through, for example, making their photos more appealing using filters, or widespread using hashtags. Emerging adults also engage in other like-seeking activities on Instagram that could be considered deceptive. For example, “likesfor-likes”, is a term in popular youth culture whereby an Instagram user likes another person’s photo primarily to increase the likelihood that the other person will reciprocate by liking one of the user’s photos in the future. Other more manipulative routes to gain more likes on Instagram involve utilizing secondary source companies that allow users to physically modify their appearance in their photos (e.g., performing “digital plastic surgery”), or to explicitly purchase followers or likes. In such cases, the user intentionally provides information that fosters a false impression about their post, constituting deception (DePaulo & Kashy, 1998; DePaulo, Kashy, Kirkendol, & Wyer, 1996). This contrasts with more typical avenues of impression management, such as highlighting relevant, positive aspects of the self without the intention to mislead (e.g., posting photos of one’s accomplishments). Providing deceptive information comprises some, but not the majority of most individuals’ social interactions (DePaulo et al., 1996), and is associated with specific types of psychopathy and personality (Stanton, Ellickson-Larew, & Watson, 2016). We posited, therefore, that there may be multiple sub-dimensions of likeseeking behavior on Instagram that may be used with differential frequency, and may derive from different psychological needs and dispositions.
1.2. Potential predictors of like-seeking on instagram There is a small body of research that helps to identify the types of individuals who are more likely to use and spend more time on Instagram. First, narcissism appears to be one of the most salient and consistent predictors of activity levels on SNSs (Ong et al., 2011) and online self-promotion (Carpenter, 2012; Lee & Sung, 2016; Mehdizadeh, 2010). Moon, Lee, Le, Choi and Sung (2016) found that among young adults in Korea, individuals who scored higher on narcissism spent more time on Instagram, posted more selfies, and updated their profile pictures more often than less narcissistic individuals. Sheldon and Bryant (2016) also found that college students with higher narcissism scores took more time editing their photos before posting them to Instagram and were more likely to use Instagram in order for surveillance (to keep tabs on others) and to be cool or popular. Some research also suggests that narcissists have less compunctions about deceiving others (Campbell, Rudich, & Sedikides, 2002; Jonason, Lyons, Baughman, & Vernon, 2014). In sum, it is plausible that narcissistic individuals engage in more like-seeking behaviors on Instagram, primarily as a way of appearing cool or increasing popularity among others. Narcissists may also be more willing to deceive other individuals by, for example, purchasing likes or followers. Second, young people’s peer relationships, and the degree that young people feel a sense of belonging within their current peer group, may affect their Instagram use. Peer belonging refers to the extent to which individuals feel connected to and valued by their peers (Newman, Lohman, & Newman, 2007). It is a salient concern in emerging adulthood (Barry, Madsen, & DeGrace, 2016) and is associated with positive psychosocial adjustment (Newman et al., 2007). Yet no research has examined the relation between peer belonging and Instagram use among young people. Strayhorn (2012) found that university students with a stronger sense of belonging, in general, tended to use SNSs (i.e., Facebook and MySpace) less often than their peers with a weaker sense of belonging. Relatedly, it is possible that emerging adults who feel a greater sense of belonging with their peers outside of Instagram may not necessarily use Instagram less, but rather feel it less necessary to engage in like-seeking behavior (i.e., seeking validation and attention from others) on Instagram. Finally, researchers have demonstrated an association between loneliness and SNS use (Pittman, 2015). Loneliness refers to a persistent, negative affective state whereby people experience feeling of emotional and social isolation (Weiss, 1973). Pittman (2015) found that undergraduate college students with higher loneliness scores tended to create and consume more content (e.g., pictures, videos) on Instagramdbut interestingly not on Facebook. In a similar vein, lonely individuals might also engage in more likeseeking behavior on Instagram overall as a way to increase social acknowledgement and validation from others. Lonelier individuals might engage in more like-seeking behavior partly due to motives to increase their visibility/popularity among peers (Sheldon & Bryant, 2016). To our knowledge, there is no research that has investigated whether deceptive behavior is related to peer belongingness and loneliness, thus, we were agnostic about the relations between these predictors and engaging in more deceptive Instagram activities. 1.3. Current project In the current project, we recruited emerging adults to complete a battery of questionnaires on their Instagram use behavior, in addition to measures of narcissism, peer belonging and loneliness. We conducted two studies, with the second a replication study. We hypothesized that emerging adults engage in a variety of different
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
behaviors in order to achieve more likes on Instagram, but that different factors would emerge that distinguish these like-seeking activities according to their frequency and associated psychological needs and traits (H1). We also predicted that participants with stronger narcissism (H2), less peer belonging (H3) and more loneliness (H4) will engage in more like-seeking behavior overall on Instagram, even after controlling for other Instagram-related behaviors such as amount of daily Instagram checking, posts and likes received. Further, we proposed that Sheldon and Bryant’s (2016) motives for Instagram use would help to explain, or mediate, the aforementioned relationships (H5). However, because of the lack of extant research to guide more specific expectations, we examined this hypothesis in an exploratory manner. 2. Study 1 2.1. Method 2.1.1. Participants Participants (N ¼ 499) were recruited to complete a survey via the online crowdsourcing portal, Amazon Mechanical Turk (mTurk). Eligibility criteria included that participants must be emerging adults (18e29 years of age). Fifty-four participants were removed from data analysis because they failed to answer at least one of our validation questions (e.g., “please check the “strongly agree” box”) correctly. Of the remaining participants, 198 participants (44.5%) were Instagram users. Of note, women were more likely to report using Instagram versus men (52.7% vs. 39.6%, respectively), c2(1) ¼ 7.28, p < 0.01. There were no other significant differences between Instagram and non-Instagram users on age, peer belonging, narcissism or loneliness (Wilks ¼ 0.99, F(4, 440) ¼ 0.70, n.s.). On average, the final sample were 25 years old (SD ¼ 2.93) and 44.4% female. One hundred and eight (54.5%) identified as Caucasian, 36 (18.2%) as Asian, 25 (12.6%) as African American, 22 (11.1%) as Latino, and 7 (3.5) as other. Participants were given $3 USD in Amazon credit for completion of the study. 2.1.2. Procedure Participants began by completing demographic questions, followed by measures of Instagram usage, peer belonging, narcissism and loneliness. 2.1.3. Measures 2.1.3.1. Instagram like-seeking behaviors. Participants were asked to indicate the extent to which they have ever done 11 different actions (e.g., “uploaded a picture”, “purchased likes”) to gain more likes on Instagram on a 3-point Likert scale with scale points including: 1 (“never”), 2 (“once or twice”) and 3 (“multiple times”). A three-point scale was chosen as opposed to a larger scale to account for the expected infrequency of some behaviors (e.g., buying likes and followers) and to increase the likelihood of obtaining a normally distributed (rather than skewed) variable. This list was derived with the help of extensive interviews with undergraduate university students at the first author’s institution who were active Instagram users. See Table 1 for all items. 2.1.3.2. Motives for Instagram use. We used Sheldon and Bryant’s (2016) scale which measures the extent to which participants use Instagram for the following four motives: surveillance/knowledge about others (7-items), documentation (6-items), coolness (4-items), and creativity (3-items) (a ¼ 0.74). On a 5-point scale from 1 (“never”) to 5 (“always”), participants documented how often they use Instagram for 20 reasons such as “to see what other people share” (surveillance/knowledge about others), “to share my life with other people” (documentation), “to become popular”
3
(coolness), and “to create art” (creativity). Confirmatory factor analyses were run for both studies, which demonstrated adequate model fit for the 4-factor solution in both Study 1 (c2 (164) ¼ 426.54; SRMR ¼ 0.09; RMSEA ¼ 0.09; CFI ¼ 0.85) and Study 2 (c2 (164) ¼ 536.35; SRMR ¼ 0.09; RMSEA ¼ 0.09; CFI ¼ 0.85). 2.1.3.3. Instagram use behavior. We asked participants several descriptive questions about their Instagram use to be used as covariates in our analyses. Items including the average number of times that they check Instagram per day, the average number of pictures that they upload to Instagram per month, the number of followers that they currently have on Instagram, the average number of likes that they receive on the pictures they post to Instagram and the highest number of likes that they have ever received on a picture posted to Instagram. 2.1.3.4. Narcissism. Participants completed the 13-item Narcissistic Personality Inventory (NPI-13; Gentile et al., 2013). Using a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), participants indicated the extent to which they agreed or disagreed with statements measuring leadership/authority, grandiose exhibitionism, and entitlement/exploitativeness. Example items include “I like having authority over people”, “I like to look at myself in the mirror” and “I expect a great deal from other people.” Participants’ scores were averaged across items with higher scores indicating more narcissism. 2.1.3.5. Peer belonging. We measured the extent to which participants feel a sense of belonging with their current friend group using 5 items from Tarrant’s (2002) Group Identity Scale. On a 5point Likert scale from 1 (“strongly agree”) to 5 (“strongly disagree”) participants report the extent to which items, such as “I have strong ties to my peer group” and “I do not fit in well with the other members in my group (reverse-scored)” describe them. 2.1.3.6. Loneliness. We measured loneliness using the UCLA Loneliness Scale, Short-Form (ULS-8; Hays & DiMatteo, 1987). This scale measures loneliness across 8 items, by having participants indicate how often statements such as “I lack companionship” and “I feel isolated from others” apply to them on a 4-point Likert scale from 1 (“never”) to 4 (“often”). 2.1.4. Analytic plan To examine H1, we conducted an exploratory factor analysis on all of our items tapping Instagram like-seeking behaviors to examine whether a multi-factor structure would distinguish different forms of like-seeking. We also ran descriptive statistics to examine the frequency of like-seeking behavior on Instagram. To examine the relations between narcissism, peer belonging, loneliness, motives for Instagram use, and like-seeking behavior indicated by H2-H5, we ran mediation models with the Hayes (2013) PROCESS macro for SPSS. This macro relies on bootstrapping analyses and we used 10,000 bootstrap samples for biascorrected bootstrap confidence intervals in all analyses. It allows the user to run mediation models with one independent variable, multiple mediators and covariates and one dependent variable. We ran separate models with peer belonging, narcissism, and loneliness as the independent variables, with the variables not included as the independent variable entered as covariates. In all models, documentation, coolness, surveillance, and creativity Instagram motives were entered as mediators. The dependent variables included deceptive and normative like-seeking behavior. Further, in all analyses we controlled for gender and age, in addition to all measured Instagram use behaviors.
4
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Table 1 Like-seeking behavior on instagram: Study 1 exploratory factor analysis, study 2 confirmatory factor analysis and item-level descriptives for studies 1 and 2. Items
1. 2. 3. 4. 5. 6.
Uploaded a picture Taken a picture Used a filter Used a hashtag Uploaded a picture at a certain time of the day Shared Instagram posts to other social networking sites (e.g., Facebook, Twitter) 7. Purchased followers 8. Purchased likes 9. Used software to modify your physical appearance 10. Taken down a picture and then put it back up at a later point 11. Liked other people’s pictures (i.e., “like for like”)
Study 1 EFA
Study 2 CFA
N(%) who engaged in behavior at least once
Factor 1: NormLS
Factor 2: DecLS
Factor 1: NormLS
Factor 2: DecLS
Study 1
Study 2
0.83 0.85 0.78 0.74 0.70 0.65
-0.11 -0.05 0.17 0.04 0.29 0.23
0.68 0.77 0.71 0.66 0.52 0.47
e e e e e e
171(83.8) 164(80.4) 146(71.6) 148(72.5) 115(56.4) 123(60.6)
242(91.3) 234(88.3) 194(73.2) 206(77.7) 165(62.3) 190(71.7)
-0.10 -0.12 0.19 0.44
0.88 0.87 0.73 0.54
e e e e
0.81 0.75 0.77 0.47
29(14.2) 24(11.8) 55(27.0) 76(37.2)
41(15.5) 37(14.0) 70(26.4) 101(38.1)
0.35
0.55
e
0.33
91(44.6)
146(55.1)
Note. Nstudy1 ¼ 198; Nstudy2 ¼ 265. NrmLS ¼ Normative Like-seeking; DecLS ¼ Deceptive Like-Seeking. Bolded numbers refer to factor loadings for the scales in which items were included.
2.2. Results Participants engaged in a variety of different like-seeking behaviors on Instagram with 90.7% of participants engaging in at least one behavior and 4.4% of participants engaging in each of the 11 behaviors. The most common behaviors included uploading (83.8%) and taking a picture (80.4%), using a hashtag (72.5%) and a filter (71.6%) and the least common behaviors included using software to modify one’s physical appearance (27.0%), and purchasing followers (14.2%) and likes (11.8%). See Table 1 for a complete list of frequencies. 2.2.1. Exploratory factor analysis An Exploratory Factor Analysis was conducted on participants’ like-seeking behavior, using a principle component solution and varimax rotation. To assess factor solution we used the minimum average partial method (MAP) and the scree test (Velicer, 1976). The scree plot utilizes the last leap in magnitude of eigenvalues as the number of factors that fit the data best. Results revealed two factors with eigenvalues greater than 1 (see Table 1). The first factor accounted for 35.18% of the variance and contained items such as “uploaded a picture”, “used a hashtag” and “used a filter.” We label this factor normative like-seeking because the majority of these activities involve using the more core communicative functions of Instagram that most users would find acceptable. The second factor accounted for 25.75% of the variance and contained items such as “purchased likes,” “used software to modify your physical appearance,” and “liked other people’s photos (“like for like”).” We label this second factor deceptive like-seeking because the majority of these items describe providing false information about the context of one’s posts.1 See Table 1 for all items and factor loadings. These factors shared a positive, but non-redundant correlation (see Table 2). 2.2.2. Mediation analyses Mediation models were conducted with both deceptive and normative like-seeking as dependent variables. We also controlled for either deceptive or normative like-seeking behavior, depending on which was the DV in the model.
1
While the two factor loadings for Item 10 (“taken down a picture and then put it up at a later time to get more likes”) were similar, we included this item in the deceptive like-seeking scale because it describes a behavior that is more calculated, manipulative and less common than items in the normative like-seeking scale. Further, results were not altered when we removed this item from our scale.
2.2.2.1. Predicting deceptive like-seeking behavior. In line with H2, a significant total effect (c path) revealed that stronger narcissism predicted more deceptive like-seeking behavior on Instagram. Consistent with H3, weaker peer belonging scores also predicted more deceptive like-seeking behavior (see Table 3). Inconsistent with H4, the relation between loneliness and deceptive likeseeking behavior was not significant. Consistent with H5, there was a significant indirect effect from narcissism to deceptive like-seeking behavior via Instagram motives (b ¼ 0.16, p < 0.01), with the direct effect remaining significant (b ¼ 0.10, p < 0.05), suggesting partial mediation. Specifically, significant indirect effects were found via more coolness and creativity motives (see Table 3 and Fig. 1). No other indirect effects were found. 2.2.2.2. Predicting normative like-seeking behavior. In line with H2, the total effect (c) of peer belonging on normative like-seeking behavior was significant, but in a positive direction. Inconsistent with H3 and H4, the c path was not significant for loneliness or narcissism (see Table 3). Follow-up analyses revealed that the c path was significant and positive for narcissism (b ¼ 0.16, p < 0.01) until deceptive likeseeking was entered into the model as a covariate. Similarly, there was a significant indirect path from narcissism to normative like-seeking behavior via Instagram motives, but only when deceptive like-seeking behavior was not included as a covariate. Significant mediators included documentation (b ¼ 0.05, 95% CI ¼ [0.01, 0.12]) and coolness motives (b ¼ 0.07, 95% CI ¼ [0.01, 0.17]). Because this suppression effect suggests that deceptive likeseeking might be playing an explanatory role in the relation between narcissism and normative like-seeking, we further employed a multiple mediator model, which revealed, first, that deceptive like-seeking was a significant mediator of the relation between narcissism and normative like-seeking (b ¼ 0.06, 95% CI ¼ [0.02, 0.13]). Second, it was involved in a complex, significant indirect path from stronger narcissism to more documentation motives to more coolness motives to more deceptive like-seeking behavior, to, finally, more normative like-seeking behavior (b ¼ 0.03, 95% CI ¼ [0.01, 0.07]). 2.3. Discussion The results from Study 1 provide initial evidence of an important distinction between normative and deceptive like-seeking behavior on Instagram. Specifically, an exploratory factor analysis
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
5
Table 2 Means, standard deviations and bivariate correlations between variables. Correlations
1. DecLS 2. NrmLS 3. Check 4. Post 5. Follow 6. Like 7. MLike 8. Doc 9. Cool 10. Surv 11. Create 12. Age 13. Narc 14. PBel 15. Lonely M SD
a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
M
SD
a
e 0.37 0.09 0.23 0.04 0.11 0.18 0.32 0.51 0.21 0.53 0.13 0.32 -0.21 0.10 1.38 0.46 0.75
0.32 e 0.24 0.19 0.12 0.14 0.15 0.48 0.47 0.33 0.35 0.01 0.25 0.14 -0.07 2.16 0.63 0.86
0.13 0.22 e 0.27 0.11 0.23 0.10 0.19 0.25 0.28 0.19 -0.03 0.22 -0.09 0.06 4.21 5.76 e
0.32 0.25 0.29 e 0.07 0.24 0.39 0.22 0.24 0.14 0.23 0.18 0.14 -0.11 0.04 5.99 9.77 e
0.14 0.04 0.08 0.07 e 0.44 0.31 0.17 0.17 0.07 0.04 -0.07 0.12 0.13 -0.12 307.53 169.00 e
0.30 0.21 0.13 0.25 0.54 e 0.60 0.20 0.23 0.06 0.18 -0.00 0.18 0.06 -0.03 34.14 95.14 e
0.23 0.22 0.13 0.23 0.55 0.89 e 0.15 0.15 -0.00 0.14 0.05 0.07 0.05 -0.06 93.76 294.65 e
0.25 0.53 0.26 0.39 0.09 0.18 0.17 e 0.69 0.60 0.40 -0.01 0.23 0.13 -0.04 3.15 1.01 0.93
0.53 0.49 0.32 0.38 0.13 0.27 0.22 0.59 e 0.55 0.54 0.07 0.35 0.10 -0.12 2.56 1.01 0.83
0.25 0.44 0.29 0.40 0.03 0.16 0.12 0.70 0.56 e 0.62 0.10 0.42 -0.05 0.10 3.45 0.72 0.83
0.46 0.39 0.19 0.27 0.12 0.24 0.21 0.50 0.66 0.44 e 0.18 0.33 -0.12 0.06 2.48 1.06 0.74
0.22 0.15 0.02 0.23 -0.10 0.02 0.03 0.22 0.16 0.20 0.24 e 0.05 -0.08 0.08 25.25 2.93 e
0.32 0.25 0.21 0.21 0.04 0.15 0.15 0.24 0.52 0.20 0.36 0.11 e 03 0.02 2.84 0.74 0.90
-0.16 0.15 0.07 0.19 0.06 0.09 0.12 0.31 0.12 0.39 0.08 0.13 0.15 e -0.45 4.01 0.64 0.89
0.04 0.02 -0.09 -0.28 0.02 -0.06 -0.08 -0.18 -0.12 -0.20 -0.11 -0.12 -0.08 -0.47 e 2.05 0.64 0.87
1.42 2.23 4.16 10.78 355.73 38.33 92.07 3.45 2.82 3.67 2.78 25.14 2.99 4.33 1.98
0.48 0.56 4.75 1.98 129.55 90.24 205.60 0.92 1.04 0.74 1.11 2.97 0.74 0.67 0.66
0.78 0.77 e e e e e 0.91 0.82 0.82 0.80 e 0.86 0.84 0.88
Note. Study 1 correlations are presented on the left side and Study 2 correlations are presented on the right side. DecLS ¼ Deceptive Like-Seeking; NrmLS ¼ Normative Likeseeking; Check ¼ # of Instagram checking per day; Post ¼ # of Instagram postings per month; Follow ¼ # of followers, Likes ¼ Average # of likes; MLikes ¼ most likes; Surv; Surveillance/knowledge about others motive; Doc ¼ Documentation motive; Cool ¼ Coolness motive; Create ¼ Creativity motive; Narc ¼ Narcissism; PBel ¼ Peer Belonging. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
suggested that the items comprising normative and deceptive likeseeking loaded on their own distinct dimensions that were moderately correlated. In addition, we observed that, while narcissistic tendencies were positively related to both normative and deceptive like-seeking, reports of a strong sense of peer belonging were negatively related to deceptive like-seeking, but positively related to normative like-seeking. In sum, deceptive versus normative like-seeking activities garnered lower levels of frequency and differentially related to peer belongingness. We also found important indirect associations between narcissism and both deceptive and normative like-seeking behavior. Most notably, more narcissistic individuals were motivated to use Instagram in attempts to become popular and to create and display their art, and these motives drove their increased engagement in deceptive like-seeking behavior. Further, deceptive like-seeking
behavior appeared to play an explanatory role in the relation between narcissism and increased normative like-seeking behaviors. Finally, no predicted findings emerged with loneliness. 3. Study 2 In Study 2, we tested our hypotheses using a replication sample in order to confirm findings from Study 1. We also conducted a confirmatory factor analysis in order to confirm the 2-factor solution of our like-seeking measure. 3.1. Method 3.1.1. Participants, procedure and materials Participants (N ¼ 325) were again recruited via mTurk.
Table 3 Direct and indirect effects on deceptive and normative like-seeking behavior.
Criterion variable Predictor variable Study 1 Deceptive Like-Seeking Narcissism Peer Belonging Loneliness Normative Like-Seeking Narcissism Peer Belonging Loneliness Study 2 Deceptive Like-Seeking Narcissism Peer Belonging Loneliness Normative Like-Seeking Narcissism Peer Belonging Loneliness
R2
Documentation motives
Coolness motives
Surveillance motives
Create motives
c
c0
Ab
LL
UL
ab
LL
UL
ab
LL
UL
ab
LL
UL
0.15** -0.13** 0.00
0.10* -0.10* -0.03
-0.03 -0.00 0.01
-0.07 -0.02 -0.01
0.00 0.02 0.04
0.05 -0.01 0.03
0.02 -0.04 -0.01
0.11 0.03 0.08
-0.00 -0.00 -0.00
-0.02 -0.02 -0.01
0.01 0.01 0.01
0.04 -0.03 -0.00
0.01 -0.07 -0.04
0.08 0.00 0.03
0.06 0.17* 0.00
0.06 0.14* 0.00
0.05 0.02 -0.02
0.01 -0.01 -0.07
0.11 0.08 0.02
0.03 0.01 0.02
-0.01 -0.01 -0.00
0.10 0.07 0.08
-0.01 -0.00 -0.00
-0.04 -0.04 -0.02
0.01 0.02 0.01
-0.00 0.00 0.00
-0.03 -0.01 -0.02
0.02 0.02 0.01
0.15* -0.20** 0.00
0.06 -0.18** 0.02
-0.01 -0.01 0.01
-0.06 -0.34 -0.01
0.03 0.00 0.06
0.17 -0.01 -0.03
0.06 -0.03 -0.11
0.30 0.01 0.03
0.00 0.01 0.00
-0.01 -0.02 -0.02
0.03 0.04 0.02
0.07 -0.01 -0.03
0.02 -0.03 -0.10
0.14 0.00 0.00
0.08 0.17** 0.13*
0.01 0.07 0.13**
0.05 0.08 0.01
-0.02 0.04 -0.04
0.15 0.14 0.05
0.07 0.01 -0.00
-0.03 -0.00 -0.03
0.22 0.05 0.01
0.00 0.01 0.00
-0.01 -0.04 -0.01
0.04 0.07 0.02
0.01 0.00 -0.00
-0.04 -0.00 -0.02
0.06 0.02 0.01
0.43
0.33
0.44
0.39
Note. c ¼ total effect of the independent variable on the dependent variable. c’ ¼ effect of independent variable on dependent variable after including mediators. ab ¼ unstandardized estimate of mediated effect. LL and UL ¼ Lower and upper limit of bias-corrected 95%. Bolded numbers indicate the presence of a significant total or indirect effect; ** ¼ p < 0.01, * ¼ p < 0.05.
6
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Coolness Motives .36
.31 a .32 .13
Creativity Motives
.15
.13 b
Documentation Motives
-.08
Surveillance Motives
-.02
Narcissism
Deceptive Like-Seeking Behavior
c(c’) .15** (.10*)
Fig. 1. Motives for Instagram use as mechanisms between narcissism and deceptive like-seeking behavior on Instagram in Study 1. Note. Parameter estimates are reported. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
Eligibility criteria stated that participants be emerging adults and possess an Instagram account. Fourteen participants were removed from data analysis because they reported not having Instagram accounts and forty-six participants were removed because they failed to answer at least one validation question correctly. The final sample consisted of 265 participants who were, on average, 25 years of age (SD ¼ 2.97) and 46.8% female. One hundred and seventy (64.2%) identified as Caucasian, 32 (12.1%) as Asian, 31 (11.7%) as African American, 31 (11.7%) as Latino, and 1 (0.01%) as other. The procedure and measures were identical to that of Study 1. 3.2. Results and discussion Consistent with the results of Study 1, participants engaged in an assortment of like-seeking behavior, with 95.5% engaging in at least one behavior and 6.8% participating in each of the 11 behaviors (see Table 1). 3.2.1. Confirmatory factor analysis We conducted a confirmatory factor analysis on the Instagram like-seeking scale using Robust Maximum Likelihood estimator in n & Muthe n, 2010), which adjusts for nonMplus7 (Muthe normality. To assess model fit, we used the chi-square statistic which contrasts the null hypothesis that all residuals in the model are null. In addition, we used absolute fit indexes such as the standardized root mean square residual (SRMR) and the root mean square error of approximation (RMSEA). Generally speaking, values between 0.05 and 0.08 represent reasonable error of approximation. We also used incremental fit indexes which measure improvement of fit by comparing our proposed model with a model that assumes no association across variables. We used the TuckerLewis Index (TLI) and the comparative fit index (CFI). Generally, values closer to 1 indicate good model fit. Factor loadings from the confirmatory factor analysis (standardized parameters estimates) are presented in Table 1. All parameters were significant and, overall, the 2-factor model had good fit (see Table 4). Further, a loglikelihood ratio test indicated that the 2-factor model has a significantly better fit to the data than a 1-factor solution (D-2 log
likelihood ¼ 348.12, df ¼ 9, p < 0.01). Finally, the factors shared a positive, but non-redundant correlation (see Table 2). 3.2.2. Predicting deceptive like-seeking behavior In accordance with H2 and H3, significant c paths indicated that higher narcissism and lower peer belonging predicted more deceptive like-seeking behavior on Instagram. Further, consistent with H5, there was a significant indirect effect from narcissism to deceptive like-seeking behavior via Instagram motives (b ¼ 0.15, p < 0.01), with the total effect (c) becoming non-significant when the indirect effect was accounted for (c’), suggesting full mediation (see Fig. 2 and Table 3). Again, higher narcissism scores predicted more coolness and creativity motives for Instagram use, which then predicted more deceptive like seeking behavior. No other indirect effects were found. 3.2.3. Predicting normative like-seeking behavior There was a significant c path for peer belonging, which predicted more normative like-seeking behavior on Instagram. Further, a significant c path revealed that greater loneliness also predicted more normative like-seeking behavior, in line with H4. Consistent with H5, there was a significant indirect effect from peer belonging to normative like-seeking via documentation motives (b ¼ 0.17, p < 0.01), with the total effect (c) becoming nonsignificant once the indirect effect (c’) was accounted for, indicating full mediation (see Table 3). Follow-up analyses demonstrated that the relation between narcissism and more normative like-seeking became significant only when deceptive like-seeking was not included as a covariate in
Table 4 Goodness-of-fit indices for instagram scale. Model
Model with 2 correlated factors
c2
82.62
df
42
Absolute fit indices
Incremental fit indices
SRMR
RMSEA
TLI
CFI
0.08
0.07
0.923
0.951
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Coolness Motives .52
.39 a .09 .04
Creativity Motives Documentation Motives Surveillance Motives
Narcissism
c(c’) .15* (.06)
7
.13
.07 b -.05 .02
Deceptive Like-Seeking Behavior
Fig. 2. Motives for Instagram use as mechanisms between narcissism and deceptive like-seeking behavior on Instagram in Study 2. Note. Parameter estimates are reported. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
the model (b ¼ 0.13, p < 0.01). Again, without deceptive likeseeking as a covariate, a significant indirect effect emerged from narcissism to normative like-seeking behavior via more documentation motives (b ¼ 0.04, 95% CI ¼ 0.01 to 0.09). Further exploration into the aforementioned associations using a multiple mediator model revealed that both stronger documentation motives (b ¼ 0.05, 95% CI ¼ [0.01, 0.10]) and more deceptive likeseeking behavior (b ¼ 0.03, 95% CI ¼ [0.01, 0.05]) were distinct mediators in the indirect relationship between narcissism and normative like-seeking behavior. However, unlike Study 1, deceptive like-seeking behavior did not help to explain (act as a second mediator in) the indirect relation between narcissism and normative like-seeking behavior via documentation motives. No other indirect associations were found. Overall, there were several noteworthy similarities between the results of Studies 1 and 2. Our CFA in the present study provided additional evidence for the empirical distinction between normative and deceptive like-seeking on Instagram, supporting H1. Deceptive like-seeking was again predicted by lower levels of peer belongingness and higher levels of narcissism, with the latter relation again mediated by coolness and creativity motives. In contrast, normative like-seeking was predicted by greater levels of narcissism, peer belongingness, and in the current study only, greater loneliness. Further, the positive relation between narcissism and normative like-seeking was again explained, at least partially, by reports of stronger documentation motives and more experience with deceptive like-seeking behavior. 4. General discussion In the current project, we examined Instagram like-seeking behavior among the site’s largest customer base, emerging adults. We demonstrated that emerging adults engage in a variety of different behaviors in order to gain attention and approval, measured in the form of “likes” received from others on Instagram, with the vast majority of participants in both our studies (90.7% and 95.5%) having engaged in at least one like-seeking behavior. This is similar to prior research suggesting that Instagram is a heightened
place of self-promotion, attention and validation-seeking among young people (Hu et al., 2014; Sheldon & Bryant, 2016). Furthermore, by utilizing both an exploratory factor analysis in Study 1 and a confirmatory factor analysis in Study 2, we established the presence of two unique types of like-seeking behavior. We labelled the first normative like-seeking behavior because it appeared that these actions are more widely accepted and perhaps young individuals would feel more comfortable admitting to peers that they had engaged in these actions, such as using hashtags or filters in order to secure more likes on Instagram. On the other hand, deceptive like-seeking behavior appeared to involve less normative, and more dishonest actions to secure Instagram likes (e.g., buying likes/followers, changing one’s physical appearance with software). Although these behaviors did not occur with the same frequency as normative like-seeking behaviors, participation in deceptive behaviors still occurred among 12e55% of the emerging adults in our studies, which is notable and concerning. In some instances, it is possible that the pursuit of attention and self-validation via Instagram likes may be positive. For example, emerging adulthood is a heightened time for identity exploration (Arnett, 2000) and engagement in more normative like-seeking behavior on Instagram, such as taking and posting pictures to gain likes, may act as an important tool to help young people try on and gain feedback about new facets of their developing identities. Further, it is important to note that, borrowing from the Facebook literature, prior research demonstrates a positive association between positive self-presentation (i.e., selectively communicating only positive, self-enhancing content on one’s wall) with general well-being (Kim & Lee, 2011). Kim and Lee also demonstrated that individuals who were more honest in their postings possessed higher well-being scores, with this relationship mediated by social support. Therefore, it is possible that the seeking of attention and self-validation via manipulation or deception (i.e., deceptive likeseeking behaviors) may predict negative adjustment outcomes including lower well-being. It will be important for future research to investigate how deceptive like-seeking may be related to important adjustment outcomes such as self-esteem, life satisfaction, and finding meaning and purpose in life (Diener, Suh, Lucas, &
8
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Smith, 1999). Although the number of (Facebook) friends or followers is related to more positive indices of adjustment (Kim & Lee, 2011), how might these relations change when individuals are inflating their friend list by purchasing fictitious followers? In both studies, we found that emerging adults higher on narcissism were more likely to engage in deceptive like-seeking behaviors, even when controlling for other activity on Instagram. These results extend prior research demonstrating that individuals higher in narcissism are more active on Instagram and engage in more self-promotional activities (Moon, Lee, Lee, Choi, & Sung, 2016; Sheldon & Bryant, 2016). Also, this relation was explained by coolness and creativity motives in both Study 1 (partial mediation) and Study 2 (full mediation). This is partially consistent with Sheldon and Bryant’s (2016) results in that they found narcissism was related to stronger coolness motives (but also stronger surveillance motives, which we didn’t find). Further, our findings extend Sheldon and Bryant’s in an important way by showing that these motives actually help to explain the link between narcissism and actual Instagram-related behaviors, suggesting more narcissistic emerging adults may be more driven to engage in deceptive like-seeking behavior for the purposes of appearing popular and showcasing their creative skills to others. Narcissism is characterized by an inflated self-concept, including a heightened sense of uniqueness (Emmons, 1984), which may manifest in a greater desire to exhibit one’s creativity (e.g., to show off one’s photography skills) to gain attention. Further, prior theory and research demonstrates that narcissists tend to use social relationships in order to build up and maintain their inflated self-concepts, including a focus on using relationships as a way to gain popularity and power over others (Campbell, 1999; Morf & Rhodewalt, 2001). In both studies, there was evidence to suggest that deceptive like-seeking played a role in explaining the relationship between heightened narcissism and normative like-seeking behavior on Instagram. Perhaps because more narcissistic people feel more comfortable with or deem it more necessary to engage in deceptive acts like buying followers on Instagram, for example, as a way to increase popularity and visibility, it follows that this might allow them to rationalize engagement in more normative likeseeking behaviors such as using hashtags. It appears, therefore, that narcissists are primarily focused on inflating their social stature on Instagram, and that their incidence of normative likeseeking may be a manifestation of their deceptive methods of achieving this goal. Future research is needed to explore this possibility. In both studies, we found that weaker feelings of peer belonging predicted more engagement in deceptive like-seeking behavior on Instagram. In contrast, stronger peer belonging predicted more engagement in normative like-seeking behavior. Furthermore, while peer belonging did predict some motives for Instagram use (somewhat less creativity motives in Study 1 and more documentation and surveillance motives in Study 2), and while documentation motives explained the relation between peer belonging and normative like-seeking behavior in Study 2, results were not consistent across studies. Thus, we do not yet have a clear understanding of the process(es) that underlie these interesting relationships. Perhaps participants lower in peer belonging engaged in more deceptive attempts at achieving likes on Instagram because they lack security and validation within their own more intimate peer circles and thus they must seek it from other, less well-known individuals on Instagram. On the contrary, perhaps individuals higher in peer belonging, who feel more secure and invested in their current peer circles, engaged in more common and acceptable behaviors in order to gain more likes and positive attention from peers. In a related vein, DePaulo
and Kashy (1998) observed that individuals with higher-quality same-sex relationships were less likely to tell lies. Relatedly, both research and theory suggest that individuals who experience stronger feelings of belonging and identification with their peer groups are more influenced by their peers and motivated to uphold the group’s reputation (Rimal & Real, 2005; Tajfel, 2010). Perhaps one way this is manifested is via seeking positive attention on Instagram, which is focused on the self (e.g., selfies) and also the peer group (e.g., posts involving one’s peers). Future research should expand upon participants’ motivations for Instagram use as well as examine participants’ desired audience when seeking likes on Instagram. For loneliness, we found that it predicted few constructs (somewhat weaker coolness motives in Study 1 and more normative like-seeking behavior in Study 2), and these results were not robust (i.e., consistent across studies). These findings are inconsistent with past research (Pittman, 2015), and suggest that the extent to which someone is lonely might not dictate their motives for Instagram use nor the degree to which they engage in likeseeking behaviors on Instagram. Perhaps, however, relations with loneliness are more nuanced and involve other contributing factors. For example, some lonely individuals might engage in like-seeking behaviors as a way to feel more connected to others, whereas other lonely individuals might be dissuaded because they do not feel that others care or are interested in them enough to actually acknowledge or like their photos or videos. Loneliness-related factors like depression may also play a role, for example, by lessening individuals’ motivation to engage in social interaction and likeseeking behavior on Instagram. Future research is needed to further understand how individuals’ psychological adjustment relates to their like-seeking behavior on Instagram. Additionally, we found consistent associations between motives for Instagram use and like-seeking behavior, with more coolness and creativity motives (and less documentation motives in Study 1) predicting more deceptive like-seeking behavior, and more documentation motives predicting more normative like-seeking behavior. Considering this, it will be important for future research to identify other predictors, or individual differences that might play a role in encouraging these motives, resulting in increased attention and validation-seeking on Instagram. Predictors that serve to discourage Instagram like-seeking behavior should also be identified. This seems especially important for deceptive likeseeking behavior, which again, appear to be a less healthy and more manipulative way to seek attention and validation using social media. One such predictor, peer belonging, was identified in this study, thus suggesting the importance of strong connection to peers in emerging adulthood for deterring potentially unhealthy use of Instagram. Limitations of this project should be noted. First, our research methodology was concurrent and correlational. Thus, future experimental and longitudinal studies are needed to tease apart the causal relationships between our variables. For instance, it is likely that emerging adults with low peer belonging feel the need to engage in more deceptive like-seeking behavior as, perhaps a form of social validation. In contrast, it is also plausible that emerging adults who engage in more of these behaviors begin to feel more isolated or rejected by their peers, or perhaps this relationship is even reciprocal. Furthermore, all our measures were based on selfreport and thus are at risk for self-reporting bias. Whereas most of our measures involved internal cognitions (feelings, motives, intentions) and states (loneliness) rather than more outward, observable behavior that could be reported by others, we could still utilize more varied data collection methods in the future to increase validity. For instance, we could monitor participants’ Instagram use, including the frequency of their activity (checks, posts)
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
and type of use (amount of filters and hashtags used) in corroboration with other self-report measures. Additionally, our sample of mTurk participants may be noted as a potential limitation. mTurk participants are more representative of the general public than standard university convenience samples, but less representative than national polls and probability samples (Berinsky, Huber, & Lenz, 2012). In the context of extrapolating to Instagram users, our recruitment materials clearly stated an eligibility for individuals between 18 and 29 years of age, which is the largest cohort of Instagram users (Duggan & Smith, 2014), although it is possible that our samples do not completely represent the population of Instagram users on the whole. It is also important to note that, while we utilized a comprehensive scale of Instagram use motives, according to the emerging adult sample who aided in its development (Sheldon & Bryant, 2016), it is possible that we did not measure all motives for use. For example, some individuals may use Instagram for economic reasons, to promote their business or brand and others may have company sponsors that pay them for showcasing products and tagging the company in Instagram posts. These individuals may be particularly motivated to use deceptive like-seeking to build their audience and obtain financial gains. That being said, we did ask participants in Study 2 about their reasons for Instagram use and found that only 7 individuals used Instagram primarily for business purposes. This does not mean, however, that there were not participants in our study, potentially those who were more narcissistic, who were motivated to gain likes on Instagram in the hopes that one day they could attain a company sponsor. Future research would benefit from including financial gain as a motive for Instagram like-seeking behavior and from examining predictors of this motive. Further, it will be worthwhile for future research to examine the extent to which different types of likeseeking behavior actually predict increases in Instagram likes or followers. In our studies, we found positive correlations between both types of like-seeking behavior with average number of likes per post and most number of likes received (see Table 2); however due to the cross-sectional nature of our studies, we were not able to assess trends in these relations over time. If it is found that individuals experience a similar or stronger increase in likes and/or followers using normative versus deceptive like-seeking behaviors, perhaps this information will help to dissuade young people from engaging in more manipulative and potentially harmful routes to obtain acceptance and validation on Instagram. To conclude, this project represents the first research on emerging adults’ like-seeking behavior on Instagram. Results point to the distinction between more normative and deceptive behaviors to gain likes from others. Findings help to identify young people who are more susceptible to engagement in more deceptive, manipulative and dishonest acts to gain attention and validation on Instagram (i.e., those with stronger narcissism and less peer belonging) and help us better understand why more narcissistic young people engage in such behaviors (i.e., to increase popularity and showcase creativity). Additional research that further examines young people’s motives for like-seeking behavior and the consequences these behaviors (particularly deceptive like-seeking) have on future adjustment will help us understand how to best proceed in addressing and perhaps reducing such behavior, as well as supporting more constructive social networking activities among emerging adults. Acknowledgements We are grateful to all the undergraduate university students who aided in the development of our Instagram like-seeking behaviors scale. Specifically, we would like to give special
9
acknowledgement to Kassandra Kropka and Christopher SterlingMurphy for their helpful insights. References Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469e480. http:// dx.doi.org/10.1037/0003-066X.55.5.469. Barry, C. M., Madsen, S. D., & DeGrace, A. (2016). Growing up with a little help from their friends in emerging adulthood. In The Oxford handbook of emerging adulthood. Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk. Political Analysis, 20(3), 351e368. Campbell, W. K. (1999). Narcissism and romantic attraction. Journal of Personality and Social Psychology, 77(6), 1254e1270. http://dx.doi.org/10.1037/00223514.77.6.1254. Campbell, W. K., Rudich, E. A., & Sedikides, C. (2002). Narcissism, self-esteem, and the positivity of self-views: Two portraits of self-love. Personality and Social Psychology Bulletin, 28(3), 358e368. http://dx.doi.org/10.1177/0146167 202286007. Carpenter, C. J. (2012). Narcissism on Facebook: Self-promotional and anti-social behavior. Personality and Individual Differences, 52(4), 482e486. http:// dx.doi.org/10.1016/j.paid.2011.11.011. DePaulo, B. M., & Kashy, D. A. (1998). Everyday lies in close and casual relationships. Journal of Personality and Social Psychology, 74(1), 63. http://dx.doi.org/10.1037/ 0022-3514.74.1.63. DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., & Wyer, M. M. (1996). Lying in everyday life. Journal of Personality and Social Psychology, 70, 979e995. http://dx.doi.org/ 10.1037/0022-3514.70.5.979. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276e302. Duggan, M., & Smith, A. (2014). Social media update 2013. Pew Research Center. Emmons, R. A. (1984). Factor analysis and construct validity of the narcissistic personality inventory. Journal of Personality Assessment, 48(3), 291e300. http:// dx.doi.org/10.1207/s15327752jpa4803_11. Gentile, B., Miller, J. D., Hoffman, B. J., Reidy, D. E., Zeichner, A., & Campbell, W. K. (2013). A test of two brief measures of grandiose narcissism: The narcissistic personality inventory-13 and the narcissistic personality inventory-16. Psychological assessment, 25(4), 1120e1136. http://dx.doi.org/10.1037/a0033192. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press. Hays, R. D., & DiMatteo, M. R. (1987). A short-form measure of loneliness. Journal of Personality Assessment, 51(1), 69e81. http://dx.doi.org/10.1207/s15327752 jpa5101_6. Hu, Y., Manikonda, L., & Kambhampati, S. (2014). What we instagram: A first analysis of instagram photo content and user types. AAAI Publications. Instagram. (2016, August). Stats. Retrieved from http://www.instagram.com/press/. Jonason, P. K., Lyons, M., Baughman, H. M., & Vernon, P. A. (2014). What a tangled web we weave: The Dark Triad traits and deception. Personality and Individual Differences, 70, 117e119. http://dx.doi.org/10.1016/j.paid.2014.06.038. Kim, J., & Lee, J.-E. R. (2011). The Facebook paths to Happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior and Social Networking, 14(6), 359e364. http://dx.doi.org/ 10.1089/cyber.2010.0374. Lee, J.-A., & Sung, Y. (2016). Hide-and-Seek: Narcissism and “Selfie”-Related behavior. Cyberpsychology, Behavior and Social Networking, 19(5), 347e351. http://dx.doi.org/10.1089/cyber.2015.0486. Mehdizadeh, S. (2010). Self-presentation 2.0: Narcissism and self-esteem on Facebook. Cyberpsychology, Behavior and Social Networking, 13(4), 357e364. http:// dx.doi.org/10.1089/cyber.2009.0257. Moon, J. H., Lee, E., Lee, J.-A., Choi, T. R., & Sung, Y. (2016). The role of narcissism in self-promotion on Instagram. Personality and Individual Differences, 101, 22e25. http://dx.doi.org/10.1016/j.paid.2016.05.042. Morf, C. C., & Rhodewalt, F. (2001). Unraveling the Paradoxes of narcissism: A dynamic self-regulatory processing model. Psychological Inquiry, 12(4), 177e196. http://dx.doi.org/10.1207/S15327965PLI1204_1. n, L. K., & Muthe n, B. O. (2010). US: Statistical analysis with latent variables: Muthe n & Muthe n. user’s guide (Vol. Version 6.). Los Angeles: Book: Muthe Newman, B. M., Lohman, B. J., & Newman, P. R. (2007). Peer group membership and a sense of belonging: Their relationship to adolescent behavior problems. Adolescence, 42(166), 241. Ong, E. Y. L., Ang, R. P., Ho, J. C. M., Lim, J. C. Y., Goh, D. H., Lee, C. S., et al. (2011). Narcissism, extraversion and adolescents’ self-presentation on Facebook. Personality and Individual Differences, 50(2), 180e185. http://dx.doi.org/10.1016/ j.paid.2010.09.022. Pittman, M. (2015). Creating, consuming, and Connecting: Examining the relationship between social media engagement and loneliness. The Journal of Social Media in Society, 4(1). Rimal, R. N., & Real, K. (2005). How behaviors are influenced by perceived norms: A test of the theory of normative social behavior. Communication Research, 32(3), 389e414. http://dx.doi.org/10.1177/0093650205275385. Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to
10
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
narcissism and contextual age. Computers in Human Behavior, 58, 89e97. http:// dx.doi.org/10.1016/j.chb.2015.12.059. Stanton, K., Ellickson-Larew, S., & Watson, D. (2016). Development and validation of a measure of online deception and intimacy. Personality and Individual Differences, 88, 187e196. http://dx.doi.org/10.1016/j.paid.2015.09.015. Strayhorn, T. L. (2012). Exploring the impact of Facebook and Myspace use on firstyear students’ sense of belonging and persistence decisions. Journal of College Student Development, 53(6), 783e796. http://dx.doi.org/10.1353/csd.2012.0078.
Tajfel, H. (2010). Social identity and intergroup relations. Cambridge [Cambridgeshire]; New York; Paris: Cambridge University Press. Tarrant, M. (2002). Adolescent peer groups and social identity. Social Development, 11(1), 110e123. http://dx.doi.org/10.1111/1467-9507.00189. Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321e327. http://dx.doi.org/10.1007/ BF02293557. Weiss, R. S. (1973). Loneliness: The experience of emotional and social isolation.
Contents lists available at ScienceDirect
Computers in Human Behavior journal homepage: www.elsevier.com/locate/comphumbeh
Full length article
Lying or longing for likes? Narcissism, peer belonging, loneliness and normative versus deceptive like-seeking on Instagram in emerging adulthood Tara M. Dumas a, *, Matthew Maxwell-Smith b, Jordan P. Davis c, Paul A. Giulietti a a b c
Huron University College at Western University, London, Ontario, Canada Western University, London, Ontario, Canada University of Illinois at Urbana-Champaign, Champaign, IL, United States
a r t i c l e i n f o
a b s t r a c t
Article history: Received 16 September 2016 Received in revised form 19 January 2017 Accepted 20 January 2017 Available online 24 January 2017
We examined the extent to which emerging adults engage in different behaviors on Instagram, a popular social networking site, to gain attention and validation from others via “likes.” We also examined individual differences in the frequency of like-seeking behavior and motives for Instagram use as mediators of these relationships. Participants (N ¼ 198 and 265 (replication study)) were recruited via an online crowdsourcing portal to complete a survey. Results demonstrated that, as predicted, participants engaged in an assortment of different like-seeking behaviors. Further, a twofactor solution emerged, with like-seeking behavior separated by whether they were normative (i.e., common or accepted, e.g., using filters or hashtags) or deceptive (e.g., buying likes or changing one’s appearance in photos using software). Deceptive like-seeking was predicted by stronger narcissism and a weaker sense of peer belonging, whereas normative like-seeking was predicted by stronger narcissism and a stronger sense of peer belonging. Further, consistent with hypotheses, significant mediators of the relation between narcissism and deceptive like-seeking included motives to use Instagram to increase popularity and showcase creativity. Results help to identify young people who are more susceptible to engaging in deceptive, potentially harmful acts to gain attention and validation on Instagram. © 2017 Elsevier Ltd. All rights reserved.
Keywords: Instagram Narcissism Peer belonging Loneliness Deception Social networks
1. Introduction Instagram is a photo and video sharing site used via mobile devices that was launched in 2010. At present, Instagram has over 500 million active monthly users, 300 million daily users, and over 95 million photos and videos are posted to Instagram per day (www.instagram.com/press/). The most common age group on Instagram are young people between the ages of 18e29 years of age, or emerging adults, who represent over one third of Instagram users (Duggan & Smith, 2014). Young people in this age group use Instagram more than any other SNS and rate Instagram as being more fun and entertaining than Facebook or Twitter (Pittman, 2015).
* Corresponding author. Huron University College, 1349 Western Road, London, Ontario, N6G 1H3, Canada. E-mail address: [email protected] (T.M. Dumas). http://dx.doi.org/10.1016/j.chb.2017.01.037 0747-5632/© 2017 Elsevier Ltd. All rights reserved.
Researchers have suggested that, as opposed to other SNS sites, Instagram use is focused more on self-presentation and promotion rather than building and maintaining relationships. Almost 25% of the photos on Instagram are focused solely on self-presentation, in the form of “selfies” (i.e., self-portraits taken by the user; Hu, Manikonda, & Kambhampati, 2014). Further, Sheldon and Bryant (2016) identified that, in addition to using Instagram to monitor other individuals (friends and otherwise), university students use Instagram primarily for self-presentation and promotion motives, including documenting their lives to others, expressing and showcasing their creativity, and increasing their popularity among peers. In this paper, we focus on the predictors of emerging adults’ engagement in like-seeking behavior on Instagram, or the extent to which they engage in behaviors to increase the number of individuals who will click a button to indicate that they “like” their photos or videos. Anecdotal evidence suggests that emerging adults engage in a variety of like-seeking behaviors, from uploading
2
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
photos at a specific time of day, to modifying their photos to make them look more attractive, to even purchasing likes or Instagram followers from secondary source sites, although no empirical research has examined the frequency and range of such behaviors. Further, no research has examined psychosocial predictors of these behaviors. Such research is important to identify which young people are most likely to seek personal validation and attention from online sources. In the current project, we examined the following questions that have not been addressed in previous research: (1) How common are different types of like-seeking behaviors among young people? (2) Are there individuals with certain peer relationships, personality traits or psychological adjustment that are more or less likely to engage in these different types of like-seeking activities on Instagram? Finally, (3) what motives explain these likeseeking behaviors? 1.1. Self-promotion and validation-seeking on instagram While the functions of Instagram overlap somewhat with other SNSs like Facebook, Instagram also differs in interesting ways. Primarily, on Facebook, the user can utilize a number of different functions (e.g., chat publicly or privately with friends, join groups, create pages for businesses or hobbies). In contrast, the primary activity on Instagram is to share photos and short videos, or to engage in visual self-presentation of one’s actual or ideal self (Hu et al., 2014), as well as viewing content from others. Because of this, Instagram has several features that help people to modify and distribute their visual content to a larger audience. The site allows users to modify their photos using different filters, so they have more control over the final image. Further, users can add hashtags (#) to their photos or videos, which allow other people to more easily find and view them, regardless of whether these people are mutual friends or “followers.” Consistent with Instagram being an outlet for self-expression, presentation, and impression management, it follows that young people on Instagram are particularly focused on validation or attention through the form of “likes.” Users may upload pictures to Instagram for the purpose of gaining likes, and use Instagram’s built in features to increase the likelihood of receiving likes through, for example, making their photos more appealing using filters, or widespread using hashtags. Emerging adults also engage in other like-seeking activities on Instagram that could be considered deceptive. For example, “likesfor-likes”, is a term in popular youth culture whereby an Instagram user likes another person’s photo primarily to increase the likelihood that the other person will reciprocate by liking one of the user’s photos in the future. Other more manipulative routes to gain more likes on Instagram involve utilizing secondary source companies that allow users to physically modify their appearance in their photos (e.g., performing “digital plastic surgery”), or to explicitly purchase followers or likes. In such cases, the user intentionally provides information that fosters a false impression about their post, constituting deception (DePaulo & Kashy, 1998; DePaulo, Kashy, Kirkendol, & Wyer, 1996). This contrasts with more typical avenues of impression management, such as highlighting relevant, positive aspects of the self without the intention to mislead (e.g., posting photos of one’s accomplishments). Providing deceptive information comprises some, but not the majority of most individuals’ social interactions (DePaulo et al., 1996), and is associated with specific types of psychopathy and personality (Stanton, Ellickson-Larew, & Watson, 2016). We posited, therefore, that there may be multiple sub-dimensions of likeseeking behavior on Instagram that may be used with differential frequency, and may derive from different psychological needs and dispositions.
1.2. Potential predictors of like-seeking on instagram There is a small body of research that helps to identify the types of individuals who are more likely to use and spend more time on Instagram. First, narcissism appears to be one of the most salient and consistent predictors of activity levels on SNSs (Ong et al., 2011) and online self-promotion (Carpenter, 2012; Lee & Sung, 2016; Mehdizadeh, 2010). Moon, Lee, Le, Choi and Sung (2016) found that among young adults in Korea, individuals who scored higher on narcissism spent more time on Instagram, posted more selfies, and updated their profile pictures more often than less narcissistic individuals. Sheldon and Bryant (2016) also found that college students with higher narcissism scores took more time editing their photos before posting them to Instagram and were more likely to use Instagram in order for surveillance (to keep tabs on others) and to be cool or popular. Some research also suggests that narcissists have less compunctions about deceiving others (Campbell, Rudich, & Sedikides, 2002; Jonason, Lyons, Baughman, & Vernon, 2014). In sum, it is plausible that narcissistic individuals engage in more like-seeking behaviors on Instagram, primarily as a way of appearing cool or increasing popularity among others. Narcissists may also be more willing to deceive other individuals by, for example, purchasing likes or followers. Second, young people’s peer relationships, and the degree that young people feel a sense of belonging within their current peer group, may affect their Instagram use. Peer belonging refers to the extent to which individuals feel connected to and valued by their peers (Newman, Lohman, & Newman, 2007). It is a salient concern in emerging adulthood (Barry, Madsen, & DeGrace, 2016) and is associated with positive psychosocial adjustment (Newman et al., 2007). Yet no research has examined the relation between peer belonging and Instagram use among young people. Strayhorn (2012) found that university students with a stronger sense of belonging, in general, tended to use SNSs (i.e., Facebook and MySpace) less often than their peers with a weaker sense of belonging. Relatedly, it is possible that emerging adults who feel a greater sense of belonging with their peers outside of Instagram may not necessarily use Instagram less, but rather feel it less necessary to engage in like-seeking behavior (i.e., seeking validation and attention from others) on Instagram. Finally, researchers have demonstrated an association between loneliness and SNS use (Pittman, 2015). Loneliness refers to a persistent, negative affective state whereby people experience feeling of emotional and social isolation (Weiss, 1973). Pittman (2015) found that undergraduate college students with higher loneliness scores tended to create and consume more content (e.g., pictures, videos) on Instagramdbut interestingly not on Facebook. In a similar vein, lonely individuals might also engage in more likeseeking behavior on Instagram overall as a way to increase social acknowledgement and validation from others. Lonelier individuals might engage in more like-seeking behavior partly due to motives to increase their visibility/popularity among peers (Sheldon & Bryant, 2016). To our knowledge, there is no research that has investigated whether deceptive behavior is related to peer belongingness and loneliness, thus, we were agnostic about the relations between these predictors and engaging in more deceptive Instagram activities. 1.3. Current project In the current project, we recruited emerging adults to complete a battery of questionnaires on their Instagram use behavior, in addition to measures of narcissism, peer belonging and loneliness. We conducted two studies, with the second a replication study. We hypothesized that emerging adults engage in a variety of different
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
behaviors in order to achieve more likes on Instagram, but that different factors would emerge that distinguish these like-seeking activities according to their frequency and associated psychological needs and traits (H1). We also predicted that participants with stronger narcissism (H2), less peer belonging (H3) and more loneliness (H4) will engage in more like-seeking behavior overall on Instagram, even after controlling for other Instagram-related behaviors such as amount of daily Instagram checking, posts and likes received. Further, we proposed that Sheldon and Bryant’s (2016) motives for Instagram use would help to explain, or mediate, the aforementioned relationships (H5). However, because of the lack of extant research to guide more specific expectations, we examined this hypothesis in an exploratory manner. 2. Study 1 2.1. Method 2.1.1. Participants Participants (N ¼ 499) were recruited to complete a survey via the online crowdsourcing portal, Amazon Mechanical Turk (mTurk). Eligibility criteria included that participants must be emerging adults (18e29 years of age). Fifty-four participants were removed from data analysis because they failed to answer at least one of our validation questions (e.g., “please check the “strongly agree” box”) correctly. Of the remaining participants, 198 participants (44.5%) were Instagram users. Of note, women were more likely to report using Instagram versus men (52.7% vs. 39.6%, respectively), c2(1) ¼ 7.28, p < 0.01. There were no other significant differences between Instagram and non-Instagram users on age, peer belonging, narcissism or loneliness (Wilks ¼ 0.99, F(4, 440) ¼ 0.70, n.s.). On average, the final sample were 25 years old (SD ¼ 2.93) and 44.4% female. One hundred and eight (54.5%) identified as Caucasian, 36 (18.2%) as Asian, 25 (12.6%) as African American, 22 (11.1%) as Latino, and 7 (3.5) as other. Participants were given $3 USD in Amazon credit for completion of the study. 2.1.2. Procedure Participants began by completing demographic questions, followed by measures of Instagram usage, peer belonging, narcissism and loneliness. 2.1.3. Measures 2.1.3.1. Instagram like-seeking behaviors. Participants were asked to indicate the extent to which they have ever done 11 different actions (e.g., “uploaded a picture”, “purchased likes”) to gain more likes on Instagram on a 3-point Likert scale with scale points including: 1 (“never”), 2 (“once or twice”) and 3 (“multiple times”). A three-point scale was chosen as opposed to a larger scale to account for the expected infrequency of some behaviors (e.g., buying likes and followers) and to increase the likelihood of obtaining a normally distributed (rather than skewed) variable. This list was derived with the help of extensive interviews with undergraduate university students at the first author’s institution who were active Instagram users. See Table 1 for all items. 2.1.3.2. Motives for Instagram use. We used Sheldon and Bryant’s (2016) scale which measures the extent to which participants use Instagram for the following four motives: surveillance/knowledge about others (7-items), documentation (6-items), coolness (4-items), and creativity (3-items) (a ¼ 0.74). On a 5-point scale from 1 (“never”) to 5 (“always”), participants documented how often they use Instagram for 20 reasons such as “to see what other people share” (surveillance/knowledge about others), “to share my life with other people” (documentation), “to become popular”
3
(coolness), and “to create art” (creativity). Confirmatory factor analyses were run for both studies, which demonstrated adequate model fit for the 4-factor solution in both Study 1 (c2 (164) ¼ 426.54; SRMR ¼ 0.09; RMSEA ¼ 0.09; CFI ¼ 0.85) and Study 2 (c2 (164) ¼ 536.35; SRMR ¼ 0.09; RMSEA ¼ 0.09; CFI ¼ 0.85). 2.1.3.3. Instagram use behavior. We asked participants several descriptive questions about their Instagram use to be used as covariates in our analyses. Items including the average number of times that they check Instagram per day, the average number of pictures that they upload to Instagram per month, the number of followers that they currently have on Instagram, the average number of likes that they receive on the pictures they post to Instagram and the highest number of likes that they have ever received on a picture posted to Instagram. 2.1.3.4. Narcissism. Participants completed the 13-item Narcissistic Personality Inventory (NPI-13; Gentile et al., 2013). Using a 5-point Likert scale ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), participants indicated the extent to which they agreed or disagreed with statements measuring leadership/authority, grandiose exhibitionism, and entitlement/exploitativeness. Example items include “I like having authority over people”, “I like to look at myself in the mirror” and “I expect a great deal from other people.” Participants’ scores were averaged across items with higher scores indicating more narcissism. 2.1.3.5. Peer belonging. We measured the extent to which participants feel a sense of belonging with their current friend group using 5 items from Tarrant’s (2002) Group Identity Scale. On a 5point Likert scale from 1 (“strongly agree”) to 5 (“strongly disagree”) participants report the extent to which items, such as “I have strong ties to my peer group” and “I do not fit in well with the other members in my group (reverse-scored)” describe them. 2.1.3.6. Loneliness. We measured loneliness using the UCLA Loneliness Scale, Short-Form (ULS-8; Hays & DiMatteo, 1987). This scale measures loneliness across 8 items, by having participants indicate how often statements such as “I lack companionship” and “I feel isolated from others” apply to them on a 4-point Likert scale from 1 (“never”) to 4 (“often”). 2.1.4. Analytic plan To examine H1, we conducted an exploratory factor analysis on all of our items tapping Instagram like-seeking behaviors to examine whether a multi-factor structure would distinguish different forms of like-seeking. We also ran descriptive statistics to examine the frequency of like-seeking behavior on Instagram. To examine the relations between narcissism, peer belonging, loneliness, motives for Instagram use, and like-seeking behavior indicated by H2-H5, we ran mediation models with the Hayes (2013) PROCESS macro for SPSS. This macro relies on bootstrapping analyses and we used 10,000 bootstrap samples for biascorrected bootstrap confidence intervals in all analyses. It allows the user to run mediation models with one independent variable, multiple mediators and covariates and one dependent variable. We ran separate models with peer belonging, narcissism, and loneliness as the independent variables, with the variables not included as the independent variable entered as covariates. In all models, documentation, coolness, surveillance, and creativity Instagram motives were entered as mediators. The dependent variables included deceptive and normative like-seeking behavior. Further, in all analyses we controlled for gender and age, in addition to all measured Instagram use behaviors.
4
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Table 1 Like-seeking behavior on instagram: Study 1 exploratory factor analysis, study 2 confirmatory factor analysis and item-level descriptives for studies 1 and 2. Items
1. 2. 3. 4. 5. 6.
Uploaded a picture Taken a picture Used a filter Used a hashtag Uploaded a picture at a certain time of the day Shared Instagram posts to other social networking sites (e.g., Facebook, Twitter) 7. Purchased followers 8. Purchased likes 9. Used software to modify your physical appearance 10. Taken down a picture and then put it back up at a later point 11. Liked other people’s pictures (i.e., “like for like”)
Study 1 EFA
Study 2 CFA
N(%) who engaged in behavior at least once
Factor 1: NormLS
Factor 2: DecLS
Factor 1: NormLS
Factor 2: DecLS
Study 1
Study 2
0.83 0.85 0.78 0.74 0.70 0.65
-0.11 -0.05 0.17 0.04 0.29 0.23
0.68 0.77 0.71 0.66 0.52 0.47
e e e e e e
171(83.8) 164(80.4) 146(71.6) 148(72.5) 115(56.4) 123(60.6)
242(91.3) 234(88.3) 194(73.2) 206(77.7) 165(62.3) 190(71.7)
-0.10 -0.12 0.19 0.44
0.88 0.87 0.73 0.54
e e e e
0.81 0.75 0.77 0.47
29(14.2) 24(11.8) 55(27.0) 76(37.2)
41(15.5) 37(14.0) 70(26.4) 101(38.1)
0.35
0.55
e
0.33
91(44.6)
146(55.1)
Note. Nstudy1 ¼ 198; Nstudy2 ¼ 265. NrmLS ¼ Normative Like-seeking; DecLS ¼ Deceptive Like-Seeking. Bolded numbers refer to factor loadings for the scales in which items were included.
2.2. Results Participants engaged in a variety of different like-seeking behaviors on Instagram with 90.7% of participants engaging in at least one behavior and 4.4% of participants engaging in each of the 11 behaviors. The most common behaviors included uploading (83.8%) and taking a picture (80.4%), using a hashtag (72.5%) and a filter (71.6%) and the least common behaviors included using software to modify one’s physical appearance (27.0%), and purchasing followers (14.2%) and likes (11.8%). See Table 1 for a complete list of frequencies. 2.2.1. Exploratory factor analysis An Exploratory Factor Analysis was conducted on participants’ like-seeking behavior, using a principle component solution and varimax rotation. To assess factor solution we used the minimum average partial method (MAP) and the scree test (Velicer, 1976). The scree plot utilizes the last leap in magnitude of eigenvalues as the number of factors that fit the data best. Results revealed two factors with eigenvalues greater than 1 (see Table 1). The first factor accounted for 35.18% of the variance and contained items such as “uploaded a picture”, “used a hashtag” and “used a filter.” We label this factor normative like-seeking because the majority of these activities involve using the more core communicative functions of Instagram that most users would find acceptable. The second factor accounted for 25.75% of the variance and contained items such as “purchased likes,” “used software to modify your physical appearance,” and “liked other people’s photos (“like for like”).” We label this second factor deceptive like-seeking because the majority of these items describe providing false information about the context of one’s posts.1 See Table 1 for all items and factor loadings. These factors shared a positive, but non-redundant correlation (see Table 2). 2.2.2. Mediation analyses Mediation models were conducted with both deceptive and normative like-seeking as dependent variables. We also controlled for either deceptive or normative like-seeking behavior, depending on which was the DV in the model.
1
While the two factor loadings for Item 10 (“taken down a picture and then put it up at a later time to get more likes”) were similar, we included this item in the deceptive like-seeking scale because it describes a behavior that is more calculated, manipulative and less common than items in the normative like-seeking scale. Further, results were not altered when we removed this item from our scale.
2.2.2.1. Predicting deceptive like-seeking behavior. In line with H2, a significant total effect (c path) revealed that stronger narcissism predicted more deceptive like-seeking behavior on Instagram. Consistent with H3, weaker peer belonging scores also predicted more deceptive like-seeking behavior (see Table 3). Inconsistent with H4, the relation between loneliness and deceptive likeseeking behavior was not significant. Consistent with H5, there was a significant indirect effect from narcissism to deceptive like-seeking behavior via Instagram motives (b ¼ 0.16, p < 0.01), with the direct effect remaining significant (b ¼ 0.10, p < 0.05), suggesting partial mediation. Specifically, significant indirect effects were found via more coolness and creativity motives (see Table 3 and Fig. 1). No other indirect effects were found. 2.2.2.2. Predicting normative like-seeking behavior. In line with H2, the total effect (c) of peer belonging on normative like-seeking behavior was significant, but in a positive direction. Inconsistent with H3 and H4, the c path was not significant for loneliness or narcissism (see Table 3). Follow-up analyses revealed that the c path was significant and positive for narcissism (b ¼ 0.16, p < 0.01) until deceptive likeseeking was entered into the model as a covariate. Similarly, there was a significant indirect path from narcissism to normative like-seeking behavior via Instagram motives, but only when deceptive like-seeking behavior was not included as a covariate. Significant mediators included documentation (b ¼ 0.05, 95% CI ¼ [0.01, 0.12]) and coolness motives (b ¼ 0.07, 95% CI ¼ [0.01, 0.17]). Because this suppression effect suggests that deceptive likeseeking might be playing an explanatory role in the relation between narcissism and normative like-seeking, we further employed a multiple mediator model, which revealed, first, that deceptive like-seeking was a significant mediator of the relation between narcissism and normative like-seeking (b ¼ 0.06, 95% CI ¼ [0.02, 0.13]). Second, it was involved in a complex, significant indirect path from stronger narcissism to more documentation motives to more coolness motives to more deceptive like-seeking behavior, to, finally, more normative like-seeking behavior (b ¼ 0.03, 95% CI ¼ [0.01, 0.07]). 2.3. Discussion The results from Study 1 provide initial evidence of an important distinction between normative and deceptive like-seeking behavior on Instagram. Specifically, an exploratory factor analysis
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
5
Table 2 Means, standard deviations and bivariate correlations between variables. Correlations
1. DecLS 2. NrmLS 3. Check 4. Post 5. Follow 6. Like 7. MLike 8. Doc 9. Cool 10. Surv 11. Create 12. Age 13. Narc 14. PBel 15. Lonely M SD
a
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
M
SD
a
e 0.37 0.09 0.23 0.04 0.11 0.18 0.32 0.51 0.21 0.53 0.13 0.32 -0.21 0.10 1.38 0.46 0.75
0.32 e 0.24 0.19 0.12 0.14 0.15 0.48 0.47 0.33 0.35 0.01 0.25 0.14 -0.07 2.16 0.63 0.86
0.13 0.22 e 0.27 0.11 0.23 0.10 0.19 0.25 0.28 0.19 -0.03 0.22 -0.09 0.06 4.21 5.76 e
0.32 0.25 0.29 e 0.07 0.24 0.39 0.22 0.24 0.14 0.23 0.18 0.14 -0.11 0.04 5.99 9.77 e
0.14 0.04 0.08 0.07 e 0.44 0.31 0.17 0.17 0.07 0.04 -0.07 0.12 0.13 -0.12 307.53 169.00 e
0.30 0.21 0.13 0.25 0.54 e 0.60 0.20 0.23 0.06 0.18 -0.00 0.18 0.06 -0.03 34.14 95.14 e
0.23 0.22 0.13 0.23 0.55 0.89 e 0.15 0.15 -0.00 0.14 0.05 0.07 0.05 -0.06 93.76 294.65 e
0.25 0.53 0.26 0.39 0.09 0.18 0.17 e 0.69 0.60 0.40 -0.01 0.23 0.13 -0.04 3.15 1.01 0.93
0.53 0.49 0.32 0.38 0.13 0.27 0.22 0.59 e 0.55 0.54 0.07 0.35 0.10 -0.12 2.56 1.01 0.83
0.25 0.44 0.29 0.40 0.03 0.16 0.12 0.70 0.56 e 0.62 0.10 0.42 -0.05 0.10 3.45 0.72 0.83
0.46 0.39 0.19 0.27 0.12 0.24 0.21 0.50 0.66 0.44 e 0.18 0.33 -0.12 0.06 2.48 1.06 0.74
0.22 0.15 0.02 0.23 -0.10 0.02 0.03 0.22 0.16 0.20 0.24 e 0.05 -0.08 0.08 25.25 2.93 e
0.32 0.25 0.21 0.21 0.04 0.15 0.15 0.24 0.52 0.20 0.36 0.11 e 03 0.02 2.84 0.74 0.90
-0.16 0.15 0.07 0.19 0.06 0.09 0.12 0.31 0.12 0.39 0.08 0.13 0.15 e -0.45 4.01 0.64 0.89
0.04 0.02 -0.09 -0.28 0.02 -0.06 -0.08 -0.18 -0.12 -0.20 -0.11 -0.12 -0.08 -0.47 e 2.05 0.64 0.87
1.42 2.23 4.16 10.78 355.73 38.33 92.07 3.45 2.82 3.67 2.78 25.14 2.99 4.33 1.98
0.48 0.56 4.75 1.98 129.55 90.24 205.60 0.92 1.04 0.74 1.11 2.97 0.74 0.67 0.66
0.78 0.77 e e e e e 0.91 0.82 0.82 0.80 e 0.86 0.84 0.88
Note. Study 1 correlations are presented on the left side and Study 2 correlations are presented on the right side. DecLS ¼ Deceptive Like-Seeking; NrmLS ¼ Normative Likeseeking; Check ¼ # of Instagram checking per day; Post ¼ # of Instagram postings per month; Follow ¼ # of followers, Likes ¼ Average # of likes; MLikes ¼ most likes; Surv; Surveillance/knowledge about others motive; Doc ¼ Documentation motive; Cool ¼ Coolness motive; Create ¼ Creativity motive; Narc ¼ Narcissism; PBel ¼ Peer Belonging. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
suggested that the items comprising normative and deceptive likeseeking loaded on their own distinct dimensions that were moderately correlated. In addition, we observed that, while narcissistic tendencies were positively related to both normative and deceptive like-seeking, reports of a strong sense of peer belonging were negatively related to deceptive like-seeking, but positively related to normative like-seeking. In sum, deceptive versus normative like-seeking activities garnered lower levels of frequency and differentially related to peer belongingness. We also found important indirect associations between narcissism and both deceptive and normative like-seeking behavior. Most notably, more narcissistic individuals were motivated to use Instagram in attempts to become popular and to create and display their art, and these motives drove their increased engagement in deceptive like-seeking behavior. Further, deceptive like-seeking
behavior appeared to play an explanatory role in the relation between narcissism and increased normative like-seeking behaviors. Finally, no predicted findings emerged with loneliness. 3. Study 2 In Study 2, we tested our hypotheses using a replication sample in order to confirm findings from Study 1. We also conducted a confirmatory factor analysis in order to confirm the 2-factor solution of our like-seeking measure. 3.1. Method 3.1.1. Participants, procedure and materials Participants (N ¼ 325) were again recruited via mTurk.
Table 3 Direct and indirect effects on deceptive and normative like-seeking behavior.
Criterion variable Predictor variable Study 1 Deceptive Like-Seeking Narcissism Peer Belonging Loneliness Normative Like-Seeking Narcissism Peer Belonging Loneliness Study 2 Deceptive Like-Seeking Narcissism Peer Belonging Loneliness Normative Like-Seeking Narcissism Peer Belonging Loneliness
R2
Documentation motives
Coolness motives
Surveillance motives
Create motives
c
c0
Ab
LL
UL
ab
LL
UL
ab
LL
UL
ab
LL
UL
0.15** -0.13** 0.00
0.10* -0.10* -0.03
-0.03 -0.00 0.01
-0.07 -0.02 -0.01
0.00 0.02 0.04
0.05 -0.01 0.03
0.02 -0.04 -0.01
0.11 0.03 0.08
-0.00 -0.00 -0.00
-0.02 -0.02 -0.01
0.01 0.01 0.01
0.04 -0.03 -0.00
0.01 -0.07 -0.04
0.08 0.00 0.03
0.06 0.17* 0.00
0.06 0.14* 0.00
0.05 0.02 -0.02
0.01 -0.01 -0.07
0.11 0.08 0.02
0.03 0.01 0.02
-0.01 -0.01 -0.00
0.10 0.07 0.08
-0.01 -0.00 -0.00
-0.04 -0.04 -0.02
0.01 0.02 0.01
-0.00 0.00 0.00
-0.03 -0.01 -0.02
0.02 0.02 0.01
0.15* -0.20** 0.00
0.06 -0.18** 0.02
-0.01 -0.01 0.01
-0.06 -0.34 -0.01
0.03 0.00 0.06
0.17 -0.01 -0.03
0.06 -0.03 -0.11
0.30 0.01 0.03
0.00 0.01 0.00
-0.01 -0.02 -0.02
0.03 0.04 0.02
0.07 -0.01 -0.03
0.02 -0.03 -0.10
0.14 0.00 0.00
0.08 0.17** 0.13*
0.01 0.07 0.13**
0.05 0.08 0.01
-0.02 0.04 -0.04
0.15 0.14 0.05
0.07 0.01 -0.00
-0.03 -0.00 -0.03
0.22 0.05 0.01
0.00 0.01 0.00
-0.01 -0.04 -0.01
0.04 0.07 0.02
0.01 0.00 -0.00
-0.04 -0.00 -0.02
0.06 0.02 0.01
0.43
0.33
0.44
0.39
Note. c ¼ total effect of the independent variable on the dependent variable. c’ ¼ effect of independent variable on dependent variable after including mediators. ab ¼ unstandardized estimate of mediated effect. LL and UL ¼ Lower and upper limit of bias-corrected 95%. Bolded numbers indicate the presence of a significant total or indirect effect; ** ¼ p < 0.01, * ¼ p < 0.05.
6
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Coolness Motives .36
.31 a .32 .13
Creativity Motives
.15
.13 b
Documentation Motives
-.08
Surveillance Motives
-.02
Narcissism
Deceptive Like-Seeking Behavior
c(c’) .15** (.10*)
Fig. 1. Motives for Instagram use as mechanisms between narcissism and deceptive like-seeking behavior on Instagram in Study 1. Note. Parameter estimates are reported. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
Eligibility criteria stated that participants be emerging adults and possess an Instagram account. Fourteen participants were removed from data analysis because they reported not having Instagram accounts and forty-six participants were removed because they failed to answer at least one validation question correctly. The final sample consisted of 265 participants who were, on average, 25 years of age (SD ¼ 2.97) and 46.8% female. One hundred and seventy (64.2%) identified as Caucasian, 32 (12.1%) as Asian, 31 (11.7%) as African American, 31 (11.7%) as Latino, and 1 (0.01%) as other. The procedure and measures were identical to that of Study 1. 3.2. Results and discussion Consistent with the results of Study 1, participants engaged in an assortment of like-seeking behavior, with 95.5% engaging in at least one behavior and 6.8% participating in each of the 11 behaviors (see Table 1). 3.2.1. Confirmatory factor analysis We conducted a confirmatory factor analysis on the Instagram like-seeking scale using Robust Maximum Likelihood estimator in n & Muthe n, 2010), which adjusts for nonMplus7 (Muthe normality. To assess model fit, we used the chi-square statistic which contrasts the null hypothesis that all residuals in the model are null. In addition, we used absolute fit indexes such as the standardized root mean square residual (SRMR) and the root mean square error of approximation (RMSEA). Generally speaking, values between 0.05 and 0.08 represent reasonable error of approximation. We also used incremental fit indexes which measure improvement of fit by comparing our proposed model with a model that assumes no association across variables. We used the TuckerLewis Index (TLI) and the comparative fit index (CFI). Generally, values closer to 1 indicate good model fit. Factor loadings from the confirmatory factor analysis (standardized parameters estimates) are presented in Table 1. All parameters were significant and, overall, the 2-factor model had good fit (see Table 4). Further, a loglikelihood ratio test indicated that the 2-factor model has a significantly better fit to the data than a 1-factor solution (D-2 log
likelihood ¼ 348.12, df ¼ 9, p < 0.01). Finally, the factors shared a positive, but non-redundant correlation (see Table 2). 3.2.2. Predicting deceptive like-seeking behavior In accordance with H2 and H3, significant c paths indicated that higher narcissism and lower peer belonging predicted more deceptive like-seeking behavior on Instagram. Further, consistent with H5, there was a significant indirect effect from narcissism to deceptive like-seeking behavior via Instagram motives (b ¼ 0.15, p < 0.01), with the total effect (c) becoming non-significant when the indirect effect was accounted for (c’), suggesting full mediation (see Fig. 2 and Table 3). Again, higher narcissism scores predicted more coolness and creativity motives for Instagram use, which then predicted more deceptive like seeking behavior. No other indirect effects were found. 3.2.3. Predicting normative like-seeking behavior There was a significant c path for peer belonging, which predicted more normative like-seeking behavior on Instagram. Further, a significant c path revealed that greater loneliness also predicted more normative like-seeking behavior, in line with H4. Consistent with H5, there was a significant indirect effect from peer belonging to normative like-seeking via documentation motives (b ¼ 0.17, p < 0.01), with the total effect (c) becoming nonsignificant once the indirect effect (c’) was accounted for, indicating full mediation (see Table 3). Follow-up analyses demonstrated that the relation between narcissism and more normative like-seeking became significant only when deceptive like-seeking was not included as a covariate in
Table 4 Goodness-of-fit indices for instagram scale. Model
Model with 2 correlated factors
c2
82.62
df
42
Absolute fit indices
Incremental fit indices
SRMR
RMSEA
TLI
CFI
0.08
0.07
0.923
0.951
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Coolness Motives .52
.39 a .09 .04
Creativity Motives Documentation Motives Surveillance Motives
Narcissism
c(c’) .15* (.06)
7
.13
.07 b -.05 .02
Deceptive Like-Seeking Behavior
Fig. 2. Motives for Instagram use as mechanisms between narcissism and deceptive like-seeking behavior on Instagram in Study 2. Note. Parameter estimates are reported. Bold ¼ p < 0.01, Italicized ¼ p < 0.05.
the model (b ¼ 0.13, p < 0.01). Again, without deceptive likeseeking as a covariate, a significant indirect effect emerged from narcissism to normative like-seeking behavior via more documentation motives (b ¼ 0.04, 95% CI ¼ 0.01 to 0.09). Further exploration into the aforementioned associations using a multiple mediator model revealed that both stronger documentation motives (b ¼ 0.05, 95% CI ¼ [0.01, 0.10]) and more deceptive likeseeking behavior (b ¼ 0.03, 95% CI ¼ [0.01, 0.05]) were distinct mediators in the indirect relationship between narcissism and normative like-seeking behavior. However, unlike Study 1, deceptive like-seeking behavior did not help to explain (act as a second mediator in) the indirect relation between narcissism and normative like-seeking behavior via documentation motives. No other indirect associations were found. Overall, there were several noteworthy similarities between the results of Studies 1 and 2. Our CFA in the present study provided additional evidence for the empirical distinction between normative and deceptive like-seeking on Instagram, supporting H1. Deceptive like-seeking was again predicted by lower levels of peer belongingness and higher levels of narcissism, with the latter relation again mediated by coolness and creativity motives. In contrast, normative like-seeking was predicted by greater levels of narcissism, peer belongingness, and in the current study only, greater loneliness. Further, the positive relation between narcissism and normative like-seeking was again explained, at least partially, by reports of stronger documentation motives and more experience with deceptive like-seeking behavior. 4. General discussion In the current project, we examined Instagram like-seeking behavior among the site’s largest customer base, emerging adults. We demonstrated that emerging adults engage in a variety of different behaviors in order to gain attention and approval, measured in the form of “likes” received from others on Instagram, with the vast majority of participants in both our studies (90.7% and 95.5%) having engaged in at least one like-seeking behavior. This is similar to prior research suggesting that Instagram is a heightened
place of self-promotion, attention and validation-seeking among young people (Hu et al., 2014; Sheldon & Bryant, 2016). Furthermore, by utilizing both an exploratory factor analysis in Study 1 and a confirmatory factor analysis in Study 2, we established the presence of two unique types of like-seeking behavior. We labelled the first normative like-seeking behavior because it appeared that these actions are more widely accepted and perhaps young individuals would feel more comfortable admitting to peers that they had engaged in these actions, such as using hashtags or filters in order to secure more likes on Instagram. On the other hand, deceptive like-seeking behavior appeared to involve less normative, and more dishonest actions to secure Instagram likes (e.g., buying likes/followers, changing one’s physical appearance with software). Although these behaviors did not occur with the same frequency as normative like-seeking behaviors, participation in deceptive behaviors still occurred among 12e55% of the emerging adults in our studies, which is notable and concerning. In some instances, it is possible that the pursuit of attention and self-validation via Instagram likes may be positive. For example, emerging adulthood is a heightened time for identity exploration (Arnett, 2000) and engagement in more normative like-seeking behavior on Instagram, such as taking and posting pictures to gain likes, may act as an important tool to help young people try on and gain feedback about new facets of their developing identities. Further, it is important to note that, borrowing from the Facebook literature, prior research demonstrates a positive association between positive self-presentation (i.e., selectively communicating only positive, self-enhancing content on one’s wall) with general well-being (Kim & Lee, 2011). Kim and Lee also demonstrated that individuals who were more honest in their postings possessed higher well-being scores, with this relationship mediated by social support. Therefore, it is possible that the seeking of attention and self-validation via manipulation or deception (i.e., deceptive likeseeking behaviors) may predict negative adjustment outcomes including lower well-being. It will be important for future research to investigate how deceptive like-seeking may be related to important adjustment outcomes such as self-esteem, life satisfaction, and finding meaning and purpose in life (Diener, Suh, Lucas, &
8
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
Smith, 1999). Although the number of (Facebook) friends or followers is related to more positive indices of adjustment (Kim & Lee, 2011), how might these relations change when individuals are inflating their friend list by purchasing fictitious followers? In both studies, we found that emerging adults higher on narcissism were more likely to engage in deceptive like-seeking behaviors, even when controlling for other activity on Instagram. These results extend prior research demonstrating that individuals higher in narcissism are more active on Instagram and engage in more self-promotional activities (Moon, Lee, Lee, Choi, & Sung, 2016; Sheldon & Bryant, 2016). Also, this relation was explained by coolness and creativity motives in both Study 1 (partial mediation) and Study 2 (full mediation). This is partially consistent with Sheldon and Bryant’s (2016) results in that they found narcissism was related to stronger coolness motives (but also stronger surveillance motives, which we didn’t find). Further, our findings extend Sheldon and Bryant’s in an important way by showing that these motives actually help to explain the link between narcissism and actual Instagram-related behaviors, suggesting more narcissistic emerging adults may be more driven to engage in deceptive like-seeking behavior for the purposes of appearing popular and showcasing their creative skills to others. Narcissism is characterized by an inflated self-concept, including a heightened sense of uniqueness (Emmons, 1984), which may manifest in a greater desire to exhibit one’s creativity (e.g., to show off one’s photography skills) to gain attention. Further, prior theory and research demonstrates that narcissists tend to use social relationships in order to build up and maintain their inflated self-concepts, including a focus on using relationships as a way to gain popularity and power over others (Campbell, 1999; Morf & Rhodewalt, 2001). In both studies, there was evidence to suggest that deceptive like-seeking played a role in explaining the relationship between heightened narcissism and normative like-seeking behavior on Instagram. Perhaps because more narcissistic people feel more comfortable with or deem it more necessary to engage in deceptive acts like buying followers on Instagram, for example, as a way to increase popularity and visibility, it follows that this might allow them to rationalize engagement in more normative likeseeking behaviors such as using hashtags. It appears, therefore, that narcissists are primarily focused on inflating their social stature on Instagram, and that their incidence of normative likeseeking may be a manifestation of their deceptive methods of achieving this goal. Future research is needed to explore this possibility. In both studies, we found that weaker feelings of peer belonging predicted more engagement in deceptive like-seeking behavior on Instagram. In contrast, stronger peer belonging predicted more engagement in normative like-seeking behavior. Furthermore, while peer belonging did predict some motives for Instagram use (somewhat less creativity motives in Study 1 and more documentation and surveillance motives in Study 2), and while documentation motives explained the relation between peer belonging and normative like-seeking behavior in Study 2, results were not consistent across studies. Thus, we do not yet have a clear understanding of the process(es) that underlie these interesting relationships. Perhaps participants lower in peer belonging engaged in more deceptive attempts at achieving likes on Instagram because they lack security and validation within their own more intimate peer circles and thus they must seek it from other, less well-known individuals on Instagram. On the contrary, perhaps individuals higher in peer belonging, who feel more secure and invested in their current peer circles, engaged in more common and acceptable behaviors in order to gain more likes and positive attention from peers. In a related vein, DePaulo
and Kashy (1998) observed that individuals with higher-quality same-sex relationships were less likely to tell lies. Relatedly, both research and theory suggest that individuals who experience stronger feelings of belonging and identification with their peer groups are more influenced by their peers and motivated to uphold the group’s reputation (Rimal & Real, 2005; Tajfel, 2010). Perhaps one way this is manifested is via seeking positive attention on Instagram, which is focused on the self (e.g., selfies) and also the peer group (e.g., posts involving one’s peers). Future research should expand upon participants’ motivations for Instagram use as well as examine participants’ desired audience when seeking likes on Instagram. For loneliness, we found that it predicted few constructs (somewhat weaker coolness motives in Study 1 and more normative like-seeking behavior in Study 2), and these results were not robust (i.e., consistent across studies). These findings are inconsistent with past research (Pittman, 2015), and suggest that the extent to which someone is lonely might not dictate their motives for Instagram use nor the degree to which they engage in likeseeking behaviors on Instagram. Perhaps, however, relations with loneliness are more nuanced and involve other contributing factors. For example, some lonely individuals might engage in like-seeking behaviors as a way to feel more connected to others, whereas other lonely individuals might be dissuaded because they do not feel that others care or are interested in them enough to actually acknowledge or like their photos or videos. Loneliness-related factors like depression may also play a role, for example, by lessening individuals’ motivation to engage in social interaction and likeseeking behavior on Instagram. Future research is needed to further understand how individuals’ psychological adjustment relates to their like-seeking behavior on Instagram. Additionally, we found consistent associations between motives for Instagram use and like-seeking behavior, with more coolness and creativity motives (and less documentation motives in Study 1) predicting more deceptive like-seeking behavior, and more documentation motives predicting more normative like-seeking behavior. Considering this, it will be important for future research to identify other predictors, or individual differences that might play a role in encouraging these motives, resulting in increased attention and validation-seeking on Instagram. Predictors that serve to discourage Instagram like-seeking behavior should also be identified. This seems especially important for deceptive likeseeking behavior, which again, appear to be a less healthy and more manipulative way to seek attention and validation using social media. One such predictor, peer belonging, was identified in this study, thus suggesting the importance of strong connection to peers in emerging adulthood for deterring potentially unhealthy use of Instagram. Limitations of this project should be noted. First, our research methodology was concurrent and correlational. Thus, future experimental and longitudinal studies are needed to tease apart the causal relationships between our variables. For instance, it is likely that emerging adults with low peer belonging feel the need to engage in more deceptive like-seeking behavior as, perhaps a form of social validation. In contrast, it is also plausible that emerging adults who engage in more of these behaviors begin to feel more isolated or rejected by their peers, or perhaps this relationship is even reciprocal. Furthermore, all our measures were based on selfreport and thus are at risk for self-reporting bias. Whereas most of our measures involved internal cognitions (feelings, motives, intentions) and states (loneliness) rather than more outward, observable behavior that could be reported by others, we could still utilize more varied data collection methods in the future to increase validity. For instance, we could monitor participants’ Instagram use, including the frequency of their activity (checks, posts)
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
and type of use (amount of filters and hashtags used) in corroboration with other self-report measures. Additionally, our sample of mTurk participants may be noted as a potential limitation. mTurk participants are more representative of the general public than standard university convenience samples, but less representative than national polls and probability samples (Berinsky, Huber, & Lenz, 2012). In the context of extrapolating to Instagram users, our recruitment materials clearly stated an eligibility for individuals between 18 and 29 years of age, which is the largest cohort of Instagram users (Duggan & Smith, 2014), although it is possible that our samples do not completely represent the population of Instagram users on the whole. It is also important to note that, while we utilized a comprehensive scale of Instagram use motives, according to the emerging adult sample who aided in its development (Sheldon & Bryant, 2016), it is possible that we did not measure all motives for use. For example, some individuals may use Instagram for economic reasons, to promote their business or brand and others may have company sponsors that pay them for showcasing products and tagging the company in Instagram posts. These individuals may be particularly motivated to use deceptive like-seeking to build their audience and obtain financial gains. That being said, we did ask participants in Study 2 about their reasons for Instagram use and found that only 7 individuals used Instagram primarily for business purposes. This does not mean, however, that there were not participants in our study, potentially those who were more narcissistic, who were motivated to gain likes on Instagram in the hopes that one day they could attain a company sponsor. Future research would benefit from including financial gain as a motive for Instagram like-seeking behavior and from examining predictors of this motive. Further, it will be worthwhile for future research to examine the extent to which different types of likeseeking behavior actually predict increases in Instagram likes or followers. In our studies, we found positive correlations between both types of like-seeking behavior with average number of likes per post and most number of likes received (see Table 2); however due to the cross-sectional nature of our studies, we were not able to assess trends in these relations over time. If it is found that individuals experience a similar or stronger increase in likes and/or followers using normative versus deceptive like-seeking behaviors, perhaps this information will help to dissuade young people from engaging in more manipulative and potentially harmful routes to obtain acceptance and validation on Instagram. To conclude, this project represents the first research on emerging adults’ like-seeking behavior on Instagram. Results point to the distinction between more normative and deceptive behaviors to gain likes from others. Findings help to identify young people who are more susceptible to engagement in more deceptive, manipulative and dishonest acts to gain attention and validation on Instagram (i.e., those with stronger narcissism and less peer belonging) and help us better understand why more narcissistic young people engage in such behaviors (i.e., to increase popularity and showcase creativity). Additional research that further examines young people’s motives for like-seeking behavior and the consequences these behaviors (particularly deceptive like-seeking) have on future adjustment will help us understand how to best proceed in addressing and perhaps reducing such behavior, as well as supporting more constructive social networking activities among emerging adults. Acknowledgements We are grateful to all the undergraduate university students who aided in the development of our Instagram like-seeking behaviors scale. Specifically, we would like to give special
9
acknowledgement to Kassandra Kropka and Christopher SterlingMurphy for their helpful insights. References Arnett, J. J. (2000). Emerging adulthood: A theory of development from the late teens through the twenties. American Psychologist, 55(5), 469e480. http:// dx.doi.org/10.1037/0003-066X.55.5.469. Barry, C. M., Madsen, S. D., & DeGrace, A. (2016). Growing up with a little help from their friends in emerging adulthood. In The Oxford handbook of emerging adulthood. Berinsky, A. J., Huber, G. A., & Lenz, G. S. (2012). Evaluating online labor markets for experimental research: Amazon.com’s Mechanical Turk. Political Analysis, 20(3), 351e368. Campbell, W. K. (1999). Narcissism and romantic attraction. Journal of Personality and Social Psychology, 77(6), 1254e1270. http://dx.doi.org/10.1037/00223514.77.6.1254. Campbell, W. K., Rudich, E. A., & Sedikides, C. (2002). Narcissism, self-esteem, and the positivity of self-views: Two portraits of self-love. Personality and Social Psychology Bulletin, 28(3), 358e368. http://dx.doi.org/10.1177/0146167 202286007. Carpenter, C. J. (2012). Narcissism on Facebook: Self-promotional and anti-social behavior. Personality and Individual Differences, 52(4), 482e486. http:// dx.doi.org/10.1016/j.paid.2011.11.011. DePaulo, B. M., & Kashy, D. A. (1998). Everyday lies in close and casual relationships. Journal of Personality and Social Psychology, 74(1), 63. http://dx.doi.org/10.1037/ 0022-3514.74.1.63. DePaulo, B. M., Kashy, D. A., Kirkendol, S. E., & Wyer, M. M. (1996). Lying in everyday life. Journal of Personality and Social Psychology, 70, 979e995. http://dx.doi.org/ 10.1037/0022-3514.70.5.979. Diener, E., Suh, E. M., Lucas, R. E., & Smith, H. L. (1999). Subjective well-being: Three decades of progress. Psychological Bulletin, 125, 276e302. Duggan, M., & Smith, A. (2014). Social media update 2013. Pew Research Center. Emmons, R. A. (1984). Factor analysis and construct validity of the narcissistic personality inventory. Journal of Personality Assessment, 48(3), 291e300. http:// dx.doi.org/10.1207/s15327752jpa4803_11. Gentile, B., Miller, J. D., Hoffman, B. J., Reidy, D. E., Zeichner, A., & Campbell, W. K. (2013). A test of two brief measures of grandiose narcissism: The narcissistic personality inventory-13 and the narcissistic personality inventory-16. Psychological assessment, 25(4), 1120e1136. http://dx.doi.org/10.1037/a0033192. Hayes, A. F. (2013). Introduction to mediation, moderation, and conditional process analysis: A regression-based approach. New York: The Guilford Press. Hays, R. D., & DiMatteo, M. R. (1987). A short-form measure of loneliness. Journal of Personality Assessment, 51(1), 69e81. http://dx.doi.org/10.1207/s15327752 jpa5101_6. Hu, Y., Manikonda, L., & Kambhampati, S. (2014). What we instagram: A first analysis of instagram photo content and user types. AAAI Publications. Instagram. (2016, August). Stats. Retrieved from http://www.instagram.com/press/. Jonason, P. K., Lyons, M., Baughman, H. M., & Vernon, P. A. (2014). What a tangled web we weave: The Dark Triad traits and deception. Personality and Individual Differences, 70, 117e119. http://dx.doi.org/10.1016/j.paid.2014.06.038. Kim, J., & Lee, J.-E. R. (2011). The Facebook paths to Happiness: Effects of the number of Facebook friends and self-presentation on subjective well-being. Cyberpsychology, Behavior and Social Networking, 14(6), 359e364. http://dx.doi.org/ 10.1089/cyber.2010.0374. Lee, J.-A., & Sung, Y. (2016). Hide-and-Seek: Narcissism and “Selfie”-Related behavior. Cyberpsychology, Behavior and Social Networking, 19(5), 347e351. http://dx.doi.org/10.1089/cyber.2015.0486. Mehdizadeh, S. (2010). Self-presentation 2.0: Narcissism and self-esteem on Facebook. Cyberpsychology, Behavior and Social Networking, 13(4), 357e364. http:// dx.doi.org/10.1089/cyber.2009.0257. Moon, J. H., Lee, E., Lee, J.-A., Choi, T. R., & Sung, Y. (2016). The role of narcissism in self-promotion on Instagram. Personality and Individual Differences, 101, 22e25. http://dx.doi.org/10.1016/j.paid.2016.05.042. Morf, C. C., & Rhodewalt, F. (2001). Unraveling the Paradoxes of narcissism: A dynamic self-regulatory processing model. Psychological Inquiry, 12(4), 177e196. http://dx.doi.org/10.1207/S15327965PLI1204_1. n, L. K., & Muthe n, B. O. (2010). US: Statistical analysis with latent variables: Muthe n & Muthe n. user’s guide (Vol. Version 6.). Los Angeles: Book: Muthe Newman, B. M., Lohman, B. J., & Newman, P. R. (2007). Peer group membership and a sense of belonging: Their relationship to adolescent behavior problems. Adolescence, 42(166), 241. Ong, E. Y. L., Ang, R. P., Ho, J. C. M., Lim, J. C. Y., Goh, D. H., Lee, C. S., et al. (2011). Narcissism, extraversion and adolescents’ self-presentation on Facebook. Personality and Individual Differences, 50(2), 180e185. http://dx.doi.org/10.1016/ j.paid.2010.09.022. Pittman, M. (2015). Creating, consuming, and Connecting: Examining the relationship between social media engagement and loneliness. The Journal of Social Media in Society, 4(1). Rimal, R. N., & Real, K. (2005). How behaviors are influenced by perceived norms: A test of the theory of normative social behavior. Communication Research, 32(3), 389e414. http://dx.doi.org/10.1177/0093650205275385. Sheldon, P., & Bryant, K. (2016). Instagram: Motives for its use and relationship to
10
T.M. Dumas et al. / Computers in Human Behavior 71 (2017) 1e10
narcissism and contextual age. Computers in Human Behavior, 58, 89e97. http:// dx.doi.org/10.1016/j.chb.2015.12.059. Stanton, K., Ellickson-Larew, S., & Watson, D. (2016). Development and validation of a measure of online deception and intimacy. Personality and Individual Differences, 88, 187e196. http://dx.doi.org/10.1016/j.paid.2015.09.015. Strayhorn, T. L. (2012). Exploring the impact of Facebook and Myspace use on firstyear students’ sense of belonging and persistence decisions. Journal of College Student Development, 53(6), 783e796. http://dx.doi.org/10.1353/csd.2012.0078.
Tajfel, H. (2010). Social identity and intergroup relations. Cambridge [Cambridgeshire]; New York; Paris: Cambridge University Press. Tarrant, M. (2002). Adolescent peer groups and social identity. Social Development, 11(1), 110e123. http://dx.doi.org/10.1111/1467-9507.00189. Velicer, W. F. (1976). Determining the number of components from the matrix of partial correlations. Psychometrika, 41(3), 321e327. http://dx.doi.org/10.1007/ BF02293557. Weiss, R. S. (1973). Loneliness: The experience of emotional and social isolation.