Belief in dangerous virtual communities as a predictor of continuance intention mediated by general and online social anxiety: The Facebook perspective

Computers in Human Behavior 48 (2015) 663–670

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Belief in dangerous virtual communities as a predictor of continuance intention mediated by general and online social anxiety: The Facebook perspective Jon-Chao Hong a, Ming-Yueh Hwang b,⇑, Chin-Hao Hsu a, Kai-Hsin Tai a, Yen-Chun Kuo a a b

Department of Industrial Education, National Taiwan Normal University, 162, Heping East Road Section 1, Taipei, Taiwan Department of Adult and Continuing Education, National Taiwan Normal University, 162, Heping East Road Section 1, Taipei, Taiwan

a r t i c l e

i n f o

Article history:

Keywords: General social anxiety Online social anxiety Belief in dangerous virtual communities Continuance intention

a b s t r a c t Despite increased understanding regarding the effects of individual and contextual factors on continuance intention, this study investigated individuals’ beliefs in dangerous virtual communities as a predictor of the related psychological symptoms, general and online social anxiety, in relation to individuals’ continuance intention to sustain participation in the social network of Facebook. Confirmatory factor analysis was applied to 230 effective questionnaires and the results revealed that belief in dangerous virtual communities was positively correlated to both general and online social anxiety, which results in a negative correlation with continuance intention. The implication was that if participants experienced high levels of both types of social anxieties, then they exhibited a low level of continuance intention. In conjunction with a number of studies, the findings suggested that belief in a dangerous virtual community serves as the antecedent of general and online social anxiety. In addition, recommendations for future research are provided by the study. Ó 2015 Elsevier Ltd. All rights reserved.

1. Introduction When social situations change to become more dangerous and threatening, individuals’ social beliefs should change accordingly. These changes in individuals’ beliefs would then activate the motivational goals of social control (Duckitt & Fisher, 2003). Kahn (1990) highlighted that some individuals believe the world to be a dangerous place and generally feel vulnerable to interpersonal sources of danger. This belief suggests that a lack of confidence in the surrounding context can lead to threats in virtual communities (Zhang, Fang, Wei, & Chen, 2010). Previous studies suggest three non-altruistic motivations for participation in virtual communities: anticipated reciprocity, increased recognition, and sense of efficacy (e.g., Kollock, 1999). Koss and Oros (1982) stated that information technology (IT) serves two functions: reflection of the belief that the offender is unable to control their behavior; and reflection of the belief that external forces are beyond the offender’s control. Thus, IT allows offenders to avoid responsibility and social disapproval regarding the offense, triggering the ⇑ Corresponding author at: P.O. Box 7-513, Taipei, Taiwan. Tel.: +886 2 2341 7409; fax: +886 2 2394 6832. E-mail addresses: [email protected] (J.-C. Hong), [email protected] (M.-Y. Hwang), [email protected] (C.-H. Hsu), [email protected] (K.-H. Tai), [email protected] (Y.-C. Kuo). http://dx.doi.org/10.1016/j.chb.2015.02.019 0747-5632/Ó 2015 Elsevier Ltd. All rights reserved.

prevalence of internet fraudulence. In addition, Duckitt (2001) proposed the influential theory that bias belief stems in part from stable, dispositional traits that are in turn reflected in social beliefs. Accordingly, this study extended the belief in a dangerous world to the belief in dangerous virtual communities (BDVC) to examine its correlations to individual differences such as social anxiety and continuance intention. Scholars suggest that social attitudes are expressions of motivational need and beliefs that have been made salient for individuals from the activation of specific social schemas (c.f. Perry, Sibley, & Duckitt, 2013). Previous studies have mostly focused on the social and psychological correlates of social network use and attitude (e.g., Moore & McElroy, 2012; Nadkarni & Hofmann, 2012; Ryan & Xenos, 2011). Existing research also shows that behavior and belief in participation vary by the type of virtual community (Partala, 2011) and pertain to anxiety-related dispositions. Online communication has become a common way of interaction among users who suffer from social anxiety, and this anxiety is frequently associated with negative perceptions when communicating online. Negative expectations during face-to-face interactions partially accounted for the relationship between social anxiety and problematic internet use (Lee & Stapinski, 2012). That is, social anxiety in virtual communities has a variety of properties consistent with the face-to-face premise. This preliminary evidence highlights

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online social anxiety to show preference, or lack thereof, in the degree of engagement in the social world. Thus, the aim of this study was to examine whether trait and state anxiety are a combinative predictor of behavior intention. Most literature on online service post-adoption behavior focuses on users’ continued use after their initial acceptance of a specific information system (Chiu & Wang, 2008). Since consumers’ experience with the system endow them new input for reevaluating the value of a specific system, post-adoption is considered as the initial adoption choice (Kim & Malhotra, 2005). Moreover, Bhattacherjee (2001) applied expectancy confirmation theory to investigate factors affecting internet continuance intention and found that post-acceptance is a vital object for successful continuation. Bhattacherjee’s study brought attention to the differences between behaviors of a user accepting an information system, versus the behavior of trying to continue using it. It was an early hypothetical study on the continued usage of IS, and brought to light new correlates between factors (Lee & Kwon, 2011). In this sense, the purpose of this study was twofold: first, to develop a conceptual framework for identifying the role of individual differences relevant to BDVC and to understand the relationship between general and online social anxiety and continuance intention; second, to determine the validity of the pathway by testing the correlations of users’ social anxiety and their intention to continue interacting with others on social networking sites. 2. Literature review Social networks (SNs) allows users to share information, such as uploaded videos or pictures, and also provides a platform for users to communicate with each other about shared content, to chat with others, and to post messages to smaller or larger audiences pre-defined by the users via friends-lists and other settings (Smock, Ellison, Lampe, & Wohn, 2011). All studies reported significant associations between personality traits and aspects of social network use (Partala, 2011). This section reviews belief in dangerous virtual communities along with general and online social anxiety in relation to continuance intention to develop a conceptual framework that guides a series of research hypotheses. 2.1. Continuance intention Continuance refers to a form of post-adoption behavior (Chang, 2013), whereas post-adoption actually refers to routinization, infusion, adaptation, and assimilation. Jasperson, Cater, and Zmud (2005) defined post-adoptive behavior as a ‘‘myriad of feature adoption decisions, feature use behaviors, and feature extension behaviors made by an individual user after an IT application has been installed, made accessible to the user, and applied by the user in accomplishing his/her work activities’’ (pp. 525–558). Hong and Tam (2006) indicated that most research on information systems use continuance intention to measure users’ likelihood to continue the use. Previous studies revealed that continuance intention exerts a key positive influence on the success of virtual communities, with effects including greater community participation in virtual communities (e.g., Algesheimer, Dholakia, & Herrmann, 2005). Furthermore, continuance intention is central to the internet context (Bhattacherjee, 2001). However, very few studies have been conducted on the relationship between user intention and social anxiety; thus, the present study included two social anxieties in the examination of continuance intentions. 2.2. General and online social anxiety Spielberger (1966) suggested that conceptual anxiety could be distinguished as trait and state anxiety. He defined trait anxiety

as an individual’s predisposition to respond and state anxiety as a transitory emotion. Individuals who experience social anxiety fear the negative appraisal from others in social or performance situations (Roth, 2004). Subsequently, they may be intimidated by situations such as speaking in public, meeting new people, talking to people in authority, or working under observation. Previous research suggested that socially anxious individuals may employ a self-protective communication style in their interactions with others, even with close friends and romantic partners (Cuming & Rapee, 2010). People with social anxiety appear to minimize self-disclosure to avoid a negative social outcome, i.e., much like a safety behavior (Arkin, Lake, & Baumgardner, 1986; Clark & Wells, 1995; Rapee & Heimberg, 1997). In the past few years, a considerable number of studies have investigated the psychological characteristics of internet users, particularly users of social networks with a focus on the personality aspects and psychological outcomes of internet use (e.g., Nadkarni & Hofmann, 2012). McKenna and Bargh (2000) speculated online social interactions to be particularly appealing to certain types of people, such as those suffering from social anxiety. To ratify McKenna and Bargh’s doubts, there is mounting evidence that social anxiety may play an essential role in the use of SNs (Buote, Wood, & Pratt, 2009). Nie (2001) discovered that internet use may reduce adolescent interpersonal interactions and communication. However, several other studies indicated that online communication is positively associated with participants’ social connectedness (Bessière, Kiesler, Kraut, & Boneva, 2008; Valkenburg & Peter, 2007). Furthermore, Torgrud et al. (2004) found that people with a high level of social anxiety receive less in the way of ‘‘social provisions’’, and Cuming and Rapee (2010) described this phenomenon as the lack of assurance in counting on others under any circumstances as a result of having low trust in the social network messages (Ellison, Steinfield, & Lampe, 2007). To study online social anxiety, Oldmeadow, Quinn, and Kowert (2013) focused specifically on interactions of social networking; they discovered that high attachment avoidance is related to less Facebook use, less openness, and less positive attitudes toward Facebook. As a result of anxiety, the availability of virtual communities does not guarantee that participants will share their feelings (Chen, 2007). Social anxiety has been conceptualized as the negative cognitive and affective response to social situations, and it is a unique predictor of endorsement that shyness interfered with willingness to be involved in a particular task (Akehurst & Thatcher, 2010). This study investigated possible moderating and mediating variables (general social anxiety) that could be relevant to further clarify the unique role of continuance intention in the process of social networking. Hence, the hypotheses are proposed as follows: H1. General social anxiety is negatively correlated to continuance intention.

Internet social anxiety is associated with perceptions of greater control and decreased risk of negative evaluation when communicating online (Lee & Stapinski, 2012). Perceived social pressure is correlated to whether to perform or not to perform a certain behavior. Kim, Chan, and Chan (2007) argued for a balanced thinking–feelings model, with cognitive and emotional factors affecting attitude and intention, indicating anxiety is negatively associated with intention to use information systems. In online discussions with anonymous users, individuals are more likely to indulge in aggressive and disrespectful behaviors. McCord, Rodebaugh, and Levinson (2014) pointed out that participants who experience a high level of social anxiety when using Facebook are reported as

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frequent users of the social networking site; such assertion reveals that social anxiety appears to affect the individuals’ continuance intention to use Facebook. H2. Online social anxiety is negatively correlated to continuance intention. Social anxiety, also termed social phobia, generally refers to an excessive fear and/or avoidance of a wide array of social situations (Liao et al., 2010). Recently, an increasing number of neuroimaging researchers turned their focus onto characterizing the brain circuits involved with social anxiety (Liao et al., 2010). If the hypothesis on a connection between the brain’s functions and social anxiety is true, then regardless of what resources the individuals have, the level of social anxiety in real life is similar to that found in the virtual community. In addition to the explanation of social anxiety related to brain function, face-to-face social anxiety can predict anxiety on Facebook, offering a less anxiety-provoking avenue to social interaction (Sheldon, 2008). Moreover, general social anxiety can be confirmed as a significant predictor of problematic internet use (Lee & Stapinski, 2012). Thus, the next research hypothesis is proposed as follows: H3. General social anxiety is positively correlated to online social anxiety. 2.3. Beliefs in dangerous virtual communities Some people view the world as a just place, believing that good and bad things come to those who deserve them (cf. Lerner & Miller, 1978). As a consequence of this belief, people who believe in a just world will often hold positive or negative attitudes toward the perceived dangerous world and exemplified with stereotypes about mental illness (Rüsch, Todd, Bodenhausen, & Corrigan, 2010). Evidence suggests that individuals who believe that the world is a dangerous place are full of interpersonal peril and tend to over-perceive threats in members of heuristically threatening groups (Maner et al., 2005). Sauer and Baer (2009) extended this line of research to examine the role of fear of emotion to account for the relationship between risk factors and thought suppression; that is, individuals with threat reasoning may consistently experience irrational fears (Vroling & de Jong, 2010). In other words, the presence of these fears seems to suggest a correlation with determinate variables such as dangerous world beliefs (Duckitt & Fisher, 2003). Most studies on technology adoption and usage continuance examine cognitive factors, leaving affective factors or the feelings of users relatively unexplored (Kim et al., 2007). They developed a thinking-feelings model to interpret information systems continuance that notes the importance of feelings in understanding and predicting human behavior. In the process of articulating this model, few studies have investigated the belief in dangerous virtual communities (BDVC), which may attribute to individuals’ feelings of social anxiety. That is, enduring cognitive process, danger schemata will produce anxiety (Chen, Lewin, & Craske, 1996). One explanation for this relationship may be related to differences in the expectation of evaluation from an online audience compared to an offline audience. Thus, it is expected that BDVC will have an intervening role in the relationship between general and online social anxiety. Therefore, this study examined the interrelatedness between individuals’ BDVC and social anxiety. The next two hypotheses are as follows: H4. BDVC is positively correlated to general social anxiety.

H5. BDVC is positively correlated to online social anxiety. 2.4. Research model The salience of different psychological needs is positive and negative user experiences (Partala, 2011). Accordingly, the current research initially assessed whether BDVC correlates with negative anxiety during Facebook use. Perhaps more importantly, the research aimed to test the correlations of social anxiety, which may be related to continuance intention. To support the argument for this double-mediated correlation, this study proposed the research model as follows (see Fig. 1). 3. Research design It is important to examine how BDVC can serve as a predictor to general social anxiety (GSA) and online social anxiety (OSA), hence, indicating continuance intention (CI). Thus, a survey study was conducted to collect sample data. 3.1. Research setting: Facebook The variety of features on Facebook suggests that it may serve different functionalities for different people, such as satisfying extrovert needs for social stimulation or facilitating social interaction. It is clear that the services and convenience provided by Facebook have made it into one of the most popular interactive online systems with millions of users (Lewis & West, 2009). Oldmeadow et al. (2013) stated that ‘‘with the growth in popularity of social networking sites (SNSs) such as Facebook, Myspace and Twitter, new forms of social interaction have emerged that differ in important ways from the offline interactions more typically studied by social psychologists’’ (pp. 1142–1149). These studies indicate that the believability of the medium influences how users view the credibility of the information presented and their possible negative reaction toward the social network (Ellison et al., 2007). On Facebook, numerous different activities are available, and users have tools to promote or establish new connections with others. Accordingly, this study adopted Facebook as a research target to understand user conditions. Focusing on the aspect of the BDVC, this study investigated users’ belief in dangerous virtual communities in relation to social anxiety and its influence on continuance intention. 3.2. Research procedure Confirmatory research was adapted for this study. After designing the research instruments, e-mail questionnaires were distributed to university students who studied in the Taipei area in Taiwan. Out of approximately ten thousand students in two public

Fig. 1. Research model.

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universities in the Taipei area, 505 students were taken as the sample for this study. The reason that university students were chosen to participate in this research is because they tend spend more time on social networks (SNs) compared to those in other age groups (Duggan & Brenner, 2013; Lenhart, Purcell, Smith, & Zickuhr, 2010). The participants completed a questionnaire packet containing a variety of measures assessing BDVC, general social anxiety, online social anxiety, and continuance intention to use Facebook. For confidentiality purposes, an informed consent was provided to participants in this study. Thereafter, data were collected within three weeks and subjected to confirmatory factor analysis (CFA) and structural equation modeling.

3.3. Research participants In total, 305 questionnaires were returned and after deleting incomplete questionnaires, 230 effective questionnaires remained. The present study achieved an effective questionnaire return rate of 46% and as for gender, 31.7% of the participants were females and 68.3% were males. As for educational level, freshmen accounted for 29.1% of the samples; sophomores accounted for 52.6% of the samples; juniors accounted for 9.1% of samples; and seniors accounted for 9.5%. Records showed that, on a daily basis, 34.3% of the individuals spent less than one hour on Facebook; 30.9% spent one to two hours; 17.4% spent two to four hours; and 17.4% of the participants spent more than four hours on Facebook every day. Comparing the proportion of samples relevant to educational background, sophomore students had the highest response rate to the questionnaire, which may be an indication that they spend more time on Facebook interacting with others.

4. Research instruments Research instruments were designed for CFA and structural equation modeling. Four measuring instruments were designed for participants to rate the extent to which they feel each statement is characteristic or true on a five-point scale.

4.1. Measuring questionnaire 4.1.1. The belief in dangerous virtual community measurement Political psychology aims to understand interdependent relationships between individuals and contexts that are influenced by beliefs, perception, in relation to information processing, socialization and attitude formation. Altemeyer (1981, 1998) found the belief in a dangerous world to be correlated with several political psychological variables (e.g., system instability, intolerance of ambiguity, need for order, fear of threats, etc.). According to the feature of social network, the scale of this study adapted ‘‘Belief in a Dangerous World Scale’’ in relation to measure the beliefs about the security of social networks (e.g., Even though I am a very cautious user of Facebook, I feel my privacy may still be exposed to the public) and interpersonal danger (e.g., I feel a lot of users on Facebook attack others with no validated reasons).

4.1.3. Continuance intention measurement The measuring items were adapted from previously validated research by Chiu, Chiu, and Chang (2007). The original instrument was translated into Chinese and modified to determine students’ continuance intention to interact with others on Facebook. 4.2. Reliability and validity analyses The study used SPSS 20 as the CFA tool to conduct descriptive statistics, items analysis, reliability analysis, validity analyses, and correlation analysis. First, internal consistency can be determined through the examination of the composite reliability (CR) of the constructs (Fornell & Larcker, 1981). All CR values in the present study ranged from .851 to .910, surpassing the suggested threshold value of .7 (Nunnally, 1978). Second, convergent validity refers to the degree to which multiple items measure one construct. Convergent validity in the present study was evaluated by checking whether (1) the average variance extracted (AVE) values were greater than .5 (Fornell & Larcker, 1981), and (2) the factor loadings of all items were significant and higher than .5 (Nunnally, 1978). All these conditions were met, indicating acceptable convergent validity. Third, item analysis, also known as a discriminative ability of item analysis, was applied to increase the validity of the questionnaire by deleting the non-discriminating items. The discriminative power of the scale was determined by its ability to discriminate the items of instrument, and the scale was examined by an independent t-test to explain the discriminative power of each item. One commonly used technique for assessing whether an item is properly discriminating is to select those in the top and bottom 27% of the subscale score distribution (Cureton, 1957) followed by a test to examine whether there exists a statistically significant difference between the two groups’ mean scores on the item to yield a t-value as the critical ratio (Himmerlfarb, 1993). If the critical ratio (t-value) is greater than 3, the discriminative power is significant. Table 1 shows that all t-values were significant (if t-value > 3.29, representing ⁄⁄⁄p < .001), signifying that all items were discriminative. All items were able to identify the degree of response of different samples, i.e., no item elimination was needed. Fourth, to evaluate the consistency of the variables, a reliability analysis of the questionnaire was identified using Cronbach’s a. According to Nunnally (1978), a Cronbach’s a value above .5 indicates an acceptable measure of reliability. Table 3 shows the Cronbach’s a values of the study. One can observe that all values were above .5, and the reliability coefficient for the entire questionnaire was .932, suggesting that the variables were reliable. The construct validity of the research instruments was established by means of CFA (Byrne, 2001). Fifth, Table 2 also shows that the means of each dimension ranged from 2.567 to 3.244, and the standard deviations were small enough to indicate that the degree of dispersion was low. 5. Research results The analysis was run in two steps. In step 1, the degree of linear relationship between each construct was calculated using the wellknown Pearson’s r coefficient of correlation. In step 2, Amos 20 was adopted for path modeling over covariance-based SEM. 5.1. Correlation analyses

4.1.2. Social anxiety measurements The two social anxiety measures are adapted from Mattick and Clarke’s (1998) Social Interaction Anxiety Scale, which taps anxiety in interpersonal and social situations. This study extended general social anxiety to online social anxiety as a situation-specific anxiety.

Table 3 shows significant correlations between BDVC, GSA, OSA, and CI, i.e., they all belonged to ‘‘high correlation’’. There was a certain degree of correlation among these continuous variables. However, BDVC, GSA and OSA were positively correlated, whereas GSA and CI, and OSA and CI were negative correlated.

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J.-C. Hong et al. / Computers in Human Behavior 48 (2015) 663–670 Table 1 Generic description.

Table 3 The correlation matrix.

Variable

Category

Frequency

Percentage

Gender

Male Female

157 73

68.3 31.7

Education

Freshman Sophomore Junior Senior

67 121 21 22

29.1 52.6 9.1 9.5

1 h & less 1–2 h (including 2 h) 2 4h (including 4 h) 4 h & more

79 71

34.3 30.9

40

17.4

40

17.4

Average number of hours spent on Facebook everyday

5.2. Model goodness of fit test This study used SEM with Amos 20 to test the goodness of fit for the model. Hair’s recommendations were adapted to set v2/df < 5 as the acceptable level, together with multiple indicators to obtain a more objective conclusion to avoid power problems from using the Chi-square test in a large sample. The model was hypothesized as v2 = 393.704, df = 130; v2/df = 3.028 with a probability level p = .02 < .05, RMSEA = .094, GFI = .837, AGFI = .785, in which GFI and AGFI were greater than .8 and RMSEA was lower than .05, suggesting that this model fitted the data the best. Hair, Black, Babin, and Anderson (2009) proposed that researchers should not only focus on the Chi-square values, but they should also consider other fitness measures. The values of fitness were all greater than .9: NFI = .813, RFI = .780, IFI = .867, TLI = .841, and CFI = .865. Overall, judging from the comprehensive indicators, the theoretical model fitted the overall pattern of the data. 5.3. Pathway analysis Fig. 2 shows the results of the path relations among the hypotheses. It is clear that all five hypotheses were supported. Fig. 2 indicates the test of the antecedent of BDVC to the

BDVC GSA OSA CI ***

BDVC

GSA

OSA

1 582*** .459*** .500***

1 .385*** .488***

1

CI

.429***

1

p < .001.

participant GSA was moderately supported, with standardized regression coefficients (SRC) of .211; the test of the antecedent of BDVC to OSA where GSA to OSA was supported, with a SRC of .331 and .501; the test of the antecedent of GSA to CI was supported, with a SRC of .302; the test of the antecedent of OSA to CI was supported, with a SRC of .423. The hypothesis was proven to be significant and, therefore, was used to verify the theoretical model. The R2 value is the percentage of variation as explained by the exogenous variable to the endogenous variables, thus, representing the predictive ability of the research model. Path coefficients and R2 values indicate the fit of the structural models with the empirical data. Fig. 2 shows the compilation of standardized path coefficients between constructs, test results, and explained variation (R2). Based on the square of multiple correlation coefficients (R2) (Byrne, 2001), the variance of explained online social anxiety by BDVC was 51.2%; the variance of explained general social anxiety by BDVC was 21.1%; and that of continuance intention explained by both social anxieties was 43.7%. Those values were more than the suggested threshold value of 10% proposed by Falk and Miller (1992). Therefore, all variables of this research had good predicting power (Hair, Sarstedt, Ringle, & Mena, 2012). 6. Discussion Online communication for those with social anxiety was made possible only through safety behavior while minimizing potential threats and the associated anxieties (Erwin, Turk, Heimberg, Fresco, & Hantula, 2004; Shepherd & Edelmann, 2005). The present study employed belief in dangerous virtual communities to examine the interrelatedness between general and online social anxiety as well as continuance intention to use Facebook. From the

Table 2 Reliability and validity with item analyses.

***

Measuring items

Mean

SD

Loading

t-value

Belief in dangerous virtual communities (BDVC): AVE = .594, CR = .879, a = .829 1. I feel that the number of users with no moral concerns has increased on Facebook 2. I feel like even though I am a very cautious user of Facebook, my privacy may still be exposed to the public 3. I feel that since Facebook names can be fictitious, the chances of one getting attacked or threatened may be higher 4. I feel a lot of users on Facebook attack others with no validated reasons 5. I feel there are more users who utilize the social network as a method to defraud

3.25 3.22 3.07 3.41 3.21 3.34

.676 .860 .868 .900 .898 .861

.791 .754 .786 .825 .694

43.700*** 47.077*** 45.645*** 44.043*** 41.266***

General social anxiety (GSA): AVE = .603, CR = .883, a = .833 1. As I imagine spending time with strangers, I feel nervous and disturbed 2. As I imagine having to carry on long conversations, I feel nervous 3. As I imagine traveling to an unfamiliar place, I feel uncomfortable 4. If someone were to introduce a new friend to me, I would feel nervous 5. When attending a crowded social event, I want to escape back home immediately

3.02 2.75 2.96 3.13 3.05 3.22

.662 .829 .806 .908 .845 .889

.759 .850 .740 .779 .750

50.269*** 55.734*** 52.356*** 54.802*** 54.864***

Online social anxiety (OSA): AVE = .669, CR = .910, a = .875 1. As I imagine having to interact with strangers in a fan club, I feel nervous 2. As I imagine chatting with others on Facebook, I feel nervous 3. As I imagine visiting an unfamiliar fan club, I feel uncomfortable 4. If someone were to suggest a friend to me on Facebook, I would feel nervous 5. If I find myself in a crowded, bustling chat room, I would want to get off line immediately

3.24 3.08 3.22 3.24 3.31 3.40

.655 .744 .762 .846 .844 .817

.845 .845 .790 .842 .767

62.789*** 63.728*** 58.075*** 59.461*** 63.004***

Continuance intention (CI): AVE = .6568, CR = .851, a = .736 1. When I need to share my person affairs, I will utilize a social network to make a post 2. I will continue using those features of Facebook to interact with friends as much as possible 3. Facebook is my favorite choice of social network, and I will continue to use it when I want to interact with friends

2.91 2.81 2.75 3.16

.728 .910 .859 .931

.848 .829 .751

46.815*** 48.604*** 51.435***

p < .001.

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that carries the boat can also sink the boat.’’ While some people choose to gain precious knowledge and positive interactive connections with others via the internet, others use the internet to harm innocent people and/or commit illegal acts. This underplays the belief in dangerous virtual communities and leads to the presentation of users’ social attitude in the virtual community. The aim of the current study was to look at Facebook users’ beliefs in dangerous virtual communities as a psychological need to understand users’ psychological anxiety that underlies their use of the virtual community. The results revealed that the increase in BDVC will increase general and online social anxiety, and the increase in the two types of social anxieties would decrease continuance intention to interact on Facebook. Fig. 2. Result of research model.

8. Contributions

particular samples, this study revealed two major results: (1) the higher the level of the participant’s BDVC, the more he or she will experience general and online social anxiety; and (2) the higher the level of the participant’s general anxiety and social anxiety, the lower the participant’s continuance intention. Previous studies indicated individuals may experience difficulty in connecting with others and become socially anxious (e.g., Wenzel, 2002). Individuals’ fear of face-to-face interaction may cause them to turn to the internet (Pierce, 2009). Moreover, Lee and Stapinski (2012) posited that anxiety over the prospect of judgments from others during social interactions may lead individuals with higher social anxiety to engage in internet use. In this sense, the results of this study indicate the average of OSA was higher than that of GSA, and GSA was positively correlated to OSA; that is, taking GSA as trait anxiety and OSA as state anxiety, the results are likely supported by the study of Saunders and Chester (2008), which provided preliminary evidence that anxiety for online communication also aggravates face-to-face avoidance The result of this study is also consistently supported by the study of Indian and Grieve (2014), which revealed that individuals who are socially anxious on Facebook also find it problematic to interact face-to-face with others. Conclusively, individuals with a higher level of social anxiety tend to have online social anxiety when actively engaged in online social networks. This study explored the relationship between BDVC and intention to continue Facebook use mediated by the two types of social anxiety. Drawing on the psychological safety or threaten literature (Zhang et al., 2010), social anxiety correlates with dangerous world beliefs (Duckitt & Fisher, 2003). Moreover, according to thinkingfeeling model (Kim et al., 2007), cognition means the mental process of thinking, including aspects such as perception, reasoning, and judgment, with the evaluative judgment of dangerous world that cause people subjectively feel powerless (Mann & Beech, 2003). In line with this, this study argued that BDVC is an important antecedent of general social anxiety and online social anxiety. Therefore, BDVC played the role of promoting the feeling of continuance intention, in which safety feeling reduces anxiety in uncertain and unknown situations (Tynan, 2005). Eventually, the result of this study revealed that both social anxieties are negatively associated with continuance intention. This result is consistent with Maner et al.’s (2005) assertion, which indicated that individuals who believe the world is a dangerous place are full of interpersonal peril and tend to over-perceive threat, reducing their interpersonal behavior.

This study makes two important contributions to the literature on social network sharing. First, this study contributes a novel, identity-centered perspective to explain BDVC’s relevance to social anxiety as reflected in behavioral intention. Specifically, this study highlights that the degree a person identifies with the aspect of BDVC will predict that person’s social anxiety related to Facebook communication and engagement. Where prior research offers limited individual-centered explanations of social anxiety mediated by BDVC to influence behavioral intention, this study shows that BDVC can explain how individuals differ in their willingness to sustain participation in a social network. Second, this study lends further support to relational perspectives on the two types of social anxieties. Where prior research has established the importance of relational characteristics in general social anxiety, this study advances our understanding on general social anxiety by showing how it promotes or inhibits online social anxiety. In this study, online social anxiety is seen to have an even more meaningful influence on continuance intention than it has been demonstrated in prior research on general social anxiety alone.

7. Conclusion

10. Limitation and future studies

In today’s internet-enabled world, virtual communities have become a commonplace. A Confucian proverb states, ‘‘The water

By using confirmatory research to design this research, e-mail questionnaires were distributed to university students who

9. Implications The greatest strength of the current study is the sample and the focus on the connection between two types of social anxiety and BDVC in the interactive social network, Facebook. Given the growing popularity of social networking sites today, this study shows that individuals with higher BDVC view both online and offline social anxieties as mediators for continuance intention, indicating the need to stress one’s BDVC for the continuation of joining SNs. Few studies have focused on this area and in line with this understanding, the research model provides quantitative grounds to understanding the correlates of BDVC to other factors, which is an important basis for researchers studying virtual communities. BDVC is an important implication on the perception of the intentions in sharing on SNs for people with a higher level of anxiety. Online social anxiety represents a sense of BDVC, making the relationships more meaningful and central to the individual’s self-concept. In this regard, the high level of BDVC with social anxiety is a deep relational evaluation of continuing intention to make a person more willing to interact in SNs. Thus, the findings from this study suggest that by having a greater understanding of how individuals vary in terms of their BDVC, social networks such as Facebook can also manage their system security more effectively.

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studied in the Taipei area. The result of this research was limited to infer those university students willing to reply the questionnaire. Samples may target to students from different areas and different educational levels and even to compare the perception and willingness between public and private university students around Taiwan. Previous research has illustrated that personality measures typically display group mean-score differences large enough to result in desirable impact (e.g., Foldes, Duehr, & Ones, 2008). Despite these benefits, individuals are motivated to elevate their personality scores in order to obtain beneficial outcomes; this is the tendency to ‘‘present an overly positive self rather than the true self’’ and it ‘‘has been generally referred to as socially desirable responding (SDR)’’ (Fan, Wong, Carroll, & Lopez, 2008, p. 790). In this regard, the social desirable distortion (SDD) can hinder the explanation of research results. Thus, future studies need to control SDD in the attempt to measure individual traits. In this study, gender was found to be a moderator of the relationship between online communication and online self-disclosure, with online communication explaining more variability in online self-disclosure for adolescent boys than girls (Chang & Heo, 2014). More research related to gender may bring greater insight into the role of positive or negative thoughts on self-presentation (Tifferet & Vilnai-Yavetz, 2014). Thus, surveying gender differences related to Facebook use may offer a new perspective. Future studies can explore social anxiety and BDVC in online social networking. Exploratory factor analysis (EFA) differs from CFA in that the former is mainly designed to explore the underlying factor structure of a set of observed variables without any preconceived model or structure of the outcome (see Child, 1990). On the other hand, CFA makes it possible to test whether a relationship between observed variables and underlying latent construct exists. In this study, CFA was selected in order to achieve the objectives: Test the hypothesis of a relationship between the selected variables and the latent variables statistically to establish whether the model fits in the particular case of our study (Harrington, 2009). Thus, to test external validity, future studies can compare those constructs of this study in different sample groups.

Acknowledgements This research is partially supported by the ‘‘Aim for the Top University Project’’ of National Taiwan Normal University (NTNU), sponsored by the Ministry of Education, Taiwan, R.O.C. and the ‘‘International Research-Intensive Center of Excellence Program’’ of NTNU and National Science Council, Taiwan, R.O.C. under Grant of NSC 103-2911-I-003-301. We also greatly appreciate the help of the students who participated in this research.

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