Correlation between university students’ online trolling behavior and online trolling victimization forms, current conditions, and personality traits

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Correlation between university students’ online trolling behavior and online trolling victimization forms, current conditions, and personality traits ⁎

Fu-Yuan Honga, , Kuang-Tsan Chengb a b

Da-Yeh University, No.168, University Rd., Dacun, Changhua 51591, Taiwan, ROC Alethiea University, No.32, Zhenli St., Danshui Dist., New Taipei City, Taiwan, ROC

AR TI CLE I NF O

AB S T R A CT

Keywords: Online trolling behavior Online trolling victimization Personality

Few studies have specifically examined online trolling behavior and the forms and current conditions of online trolling victimization that may develop among university students, as well as the correlation of these to personality traits. The valid sample included 285 university students, with 80.6% and 19.3% being male and female, respectively. The research results are: 1. Online trolling behavior is more common in those who more frequently post text information on Facebook than those who do not; 203 (71.2%) and 211 (74.0%) experienced at least 1 instance of online trolling behavior or being an online trolling victim, respectively, in the previous week; 2. University students’ online trolling behavior types are ranked by quantity as evocative trolling, malicious trolling, obstruction trolling, and pathological trolling; 3. University students’ online trolling victimization types are ranked by quantity as identity victimization, dissemination victimization, malicious victimization, and obstruction victimization; 4. Sense of inferiority is a significant predictive variable for online trolling behavior and online trolling victimization. At the same time, social extraversion and depression significantly and positively predict online trolling behavior. Based on the foregoing results, the study proposed discussion and recommendations for university students and future research.

The earliest term for trolling referred to a method of fishing, with people dragging bait behind a boat to attract fish (Oxford English Dictionary, 2015). In fairy tales, a troll was a monster that hid under bridges to scare and lunge at unknown passers-bys (Ansong et al., 2013; Herring et al., 2002). Donath (1999) was the first to see trolling behavior as a personal identity fraud game (p. 45). If trolling behavior is applied to the Internet context, then online trolling can broadly refer to hiding in the Internet environment to utilize hot-button issues to make other Internet users become excessively emotional or stupid, or to intentionally anger others to get emotional responses from them, or to oppose other Internet users with predictable or unpredictable behaviors; if someone falls into the trap, then the troll(s) become even more extreme (Buckels et al., 2014; Griffiths, 2014; Morrissey, 2010). However, there are few studies in the literature covering specific behavioral features, types, and frequencies of online trolling behavior, and there are no systematic analyses of online trolling victimization. Therefore, this study used retrospective methods to analyze possible online trolling behavior and online trolling victimization for university students in the previous week, in order to clarify their concepts of online trolling behavior and online trolling victimization, employing this as a basis of reference and direction to understand and handle online trolling behavior of university students in the future. Past studies have found that online trolling behavior may appear in all ages and backgrounds (Hardaker, 2013), but younger men

⁎

Corresponding author. E-mail addresses: [email protected] (F.-Y. Hong), [email protected] (K.-T. Cheng).

https://doi.org/10.1016/j.tele.2017.12.016 Received 13 September 2017; Received in revised form 28 November 2017; Accepted 20 December 2017 0736-5853/ © 2017 Elsevier Ltd. All rights reserved.

Please cite this article as: Hong, F.-Y., Telematics and Informatics (2017), https://doi.org/10.1016/j.tele.2017.12.016

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are more likely to exhibit online trolling behavior (Thacker and Griffiths, 2012). An online survey of 2000 adolescents in the age range of 14–18 years showed that 1/3 of adolescents engaged in online trolling in the last six months, and 1/10 admitted that they were trolls (Rice, 2013). This shows that online trolling behavior may appear more frequently in young male high school students, yet because university students more frequently use the Internet, they may also be a high-risk group for online trolling behavior. Therefore, this study explored this phenomenon with the university students as the sample. In online interaction in non-mainstream online environments, including Wikipedia (Shachaf and Hara, 2010), feminist forums (Balka, 1993; Herring et al., 2002), and gaming worlds (Thacker and Griffiths, 2012), and platforms that allow groups to interact, post information, and chat, such as Facebook, Twitter, Whatsapp, and Instangram (Ansong et al., 2013), online users are more susceptible to harm from trolling behavior. In sum, factors such as gender, grade, and different online platforms may all affect online trolling behavior and online trolling victimization, which this study included in its consideration. Researchers have proposed concepts and measurement tools for online trolling behavior and have further analyzed the relationships among Dark Tetrad (Buckels et al., 2014), self-esteem (Thacker and Griffiths, 2012), and online trolling behavior. However, few studies have empirically compiled a multifaceted measurement tool for online trolling behavior and online trolling victimization, or explored the relationships among online trolling behavior, online trolling victimization and social extraversion, unstable emotions, and unhealthy psychological characters. Results of this present study can further expand the field of online trolling behavior and online trolling victimization, which has been overlooked, and provide a preliminary exploration for future studies.

2. Literature review 2.1. The nature of online trolling behavior and online trolling victimization Forms of online trolling behavior include irritating behavior, gender discrimination/racism, and intentional falsification and misleading claims (Thacker and Griffiths, 2012). More specifically, online trolls tend to deliberately post and disseminate provocative, offensive, incorrect, deliberately falsified, or apparently genuine information, and they may also engage in Internet abuse and design predictable flame wars, elicit pointless arguments, or use information incorrectly to make others devote themselves to useless, meaningless, and time-consuming discussions, even leading to negative behavioral responses or violent responses (Ansong et al., 2013, p. 42; Bishop, 2013; Buckels et al., 2014; Herring et al., 2002, p. 373; Morrissey, 2010). Aside from posting and disseminating information, online trolling behavior may include many Internet behaviors that interfere with other gaming interests (Griffiths, 2014). Adrian (2010) believed that a person who shows trolling behavior in online gaming could be considered a griefer; a troll in a game wants to obstruct team hunts or goals; and a troll can describe a person who wants to destroy the game. Since online trolling behavior is a form of cyberbullying (Griffiths, 2014; Morrissey, 2010), cyberbullies tend to have clearer identities and simpler intents (Lenhardt, 2013). Therefore, online trolling behavior in this study is an independent concept among these antisocial forms online. In terms of tools to measure online trolling behavior, Buckels et al. (2014) compiled the Global Assessment of Internet Trolling (GAIT) scale with four categories of questions. Although the scale had satisfactory reliability, stressed trolling experiences and various preferences of trolling and identification with Internet subcultures, and proposed two scenarios of online text posts and game texts, it did not include common and diverse trolling characteristics, such as being hypocritical, antipathizing, deviating, cross-posting, annoying, and endangering (Ansong et al., 2013). Therefore, this study utilizes the two scenarios of online text posting and game text interaction to expand and deepen the dimensions of online trolling behavior in compiling an online trolling behavior scale. Furthermore, past studies have not used university students’ perspectives to understand the current conditions and frequencies of online trolling victimization; thus, the study also compiles an online trolling victimization scale

2.2. Online trolling behavior, online trolling victimization, and personality Online trolling behavior is a form of cyberbullying (Griffiths, 2014; Morrissey, 2010), and cyberbullies may have more antisocial personality traits (Fanti et al., 2012; Van Baardewijk et al., 2009) as well as greater narcissistic deprivation and hostile beliefs (Ang et al., 2011). Similarly, the noxious Dark Tetrad of personality is also significantly correlated to adolescent bullying activity (Fanti and Kimonis, 2013). Therefore, malicious abuse, Machiavellianism, neuroticism, and psychopathy, as parts of the Dark Tetrad, all show a significant positive correlation with online trolling (Buckels et al., 2014). One main reason for this may be that online trolls seek to be successful in provoking, attacking, lying to, sabotaging, and threatening other online users (Bishop, 2013; Buckels et al., 2014; Hardaker, 2010; Herring et al., 2002). On the other hand, online trolls and abusers all see the pain of others as their happiness in inflicting pain; these abusers want enjoyment and see the Internet as their playground (Buckels et al., 2014). Therefore, online trolling behavior may arise from boredom, seeking attention, entertainment, a desire to affect the social network, and deriving pleasure from harming websites and users (Shachaf and Hara, 2010; Thacker and Griffiths, 2012). This may mean that online trolls prefer to interact and chat with others online, but few studies have explored the correlations between online trolling behavior and online trolling victimization and extraversion, emotional instability, and unhealthy psychology. Based on the foregoing literature, this study believes that online trolling behavior and online trolling victimization may involve the personality traits of extraversion, unstable emotions, and poor psychological health.

2

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3. Method 3.1. Participants University students were used as subjects in the pilot study for the measurement tools in this study, with 206 valid questionnaires. Among them, 88 were men (42.7%) and 118 were women (57.3%). The reliability and validity analysis of the scale used herein were based on the results of the pilot sample. The subjects in the main study were sampled from three universities in Taiwan; 300 questionnaires were released and 285 valid questionnaires were retrieved. The make-up of the respondents were: 228 were men (80.0%), 57 were women (20.0%), 69 (24.2%) were first-year university students, 89 (31.2%) were second-year students, 66 (23.2%) were third-year students, and 61 (21.4%) were fourth-year students. The age range was primarily 18–22 years, which met the study’s requirement of university students as research subjects.

3.2. Measures The measurement variables included university gender, year, websites where they posted information, online trolling behavior, online trolling victimization, social extraversion, sense of inferiority, neurotic, and depression. Students were asked to rank where they most frequently posted text information for Facebook, Line, YouTube, news websites, forums, BBS, blogs, instant messenger, interactive online games, Wikipedia, and other types of websites. Next, the study conducted reliability and validity analyses of the online trolling behavior scale and online trolling victimization scale, with an eigenvalue greater than 1 and scree test as the factor selection criteria. Orthogonal rotations were used for factor analysis. Questions were discarded if factor loading was smaller than .5 and showed double loading (Tabachnick and Fidell, 2007).

3.3. Online trolling behavior scale and online trolling victimization scale Both scales referred to Buckels et al.’s (2014) Global Assessment of Internet Trolling (GAIT) and Ansong et al.’s (2013) online trolling behavior strategies, simultaneously using the two contexts of online text statements and game text interactions to expand and deepen the levels of online trolling behavior. The university student subjects were asked to respond to the amount of online trolling behavior and online trolling victimization instances per week, and the response dimensions were six selections of 0 times (0 points), 1–2 times (1 point), 3–4 times (2 points), 5–6 times (3 points), 7–8 times (4 points), and more than 9 times (5 points). The online trolling behavior scale originally included 34 questions. After factor analysis, the KMO measure of sampling adequacy was .93, and the Bartlett test of sphericity χ2(300) = 6203.492 (p < .001), showing strong fit of factor analysis. The scale included four factors, malicious trolling (12 questions), obstruction trolling (5 questions), evocative trolling (5 questions), and pathological trolling (3 questions), which explained a total of 70.68% variance, with a total of 25 questions. Malicious trolling refers to a person transmitting, posting, or publishing online text messages that maliciously sabotage others’ games, provoking or attacking through tricks, lies, and harassment, or threatening others. Obstruction trolling refers to personal transmission, posting, or publishing of online text messages to obstruct other peoples’ usage of the Internet and to move the positions of others. Evocative trolling refers to personal transmission, posting, or publishing of Internet text information to make others agree, discuss, and create resonance. Pathological trolling refers to personal adoption of attitudes and perspectives contrarian to usual and normal views to sensitive, serious, or beautiful matters. The internal consistency of Cronbach’s α of all questions in the online trolling behavior scale was .95, which makes the reliability and validity of this scale pretty good. The online trolling victimization scale originally included 32 questions. After factor analysis, the KMO measure of sampling adequacy was .91, and the Bartlett test of sphericity χ2(378) = 6930.78 (p < .001), showing factor analysis fit. The scale included four factors, malicious victimization (11 questions), identity victimization (7 questions), obstruction victimization (5 questions), and dissemination victimization (3 questions), which explained a total of 68.79% variance, with a total of 28 questions. Malicious victimization refers to personally noticing or receiving text messages transmitted, posted, or published by others, with such text maliciously sabotaging the game, provoking, attacking, tricking, lying, harassing, or threatening, resulting in victimization. Identity victimization refers to when one person believes online statements as being true, thereby eliciting negative emotions and affecting personal thoughts. Obstruction victimization refers to when in online interactive games, a person notices or receives text messages transmitted, posted, or published by others, resulting in victimization. Dissemination victimization refers to a person who receives false or junk information online, causing a loss of energy and time when paying attention. The internal consistency of Cronbach’s α of all questions in the online trolling victimization scale was .95, and thus the reliability and validity of this scale is pretty good.

3.4. Lai’s personality test Lai’s Personality Test contained 150 questions in 15 sub-scales. Each sub-scale represented one personality trait, with retest reliability between 0.71 and 0.93, and with sub-scale reliability ranging from 0.62 to 0.81 (Lai and Lai, 2003). The study only used the four sub-scales of social extraversion, sense of inferiority, neurotic, and depressive in Lai’s Personality Test, with each sub-scale containing 10 questions for a total of 40 questions. Scores are computed by 2 points for “yes,” 1 point for “?” in the middle, and 0 points for “No.” The internal consistency reliabilities of the sub-scales were .81, .77, .80, and .87, respectively 3

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4. Results 4.1. Analysis of current conditions of online trolling behavior and online trolling victimization In websites where university students more frequently post text information, 133 (46.7%) used Facebook, 136 (47.7%) used Line, and 16 (5.6%) used YouTube, news websites, forums, BBS, blogs, instant messengers, interactive online games, Wikipedia, and others. For university students who used Facebook, Line, and other three types, they showed significant differences in terms of online trolling behavior (F = 4.79, p < .05) and online trolling victimization (F = 3.30, p < .05). A post hoc comparison presented that those who more frequently posted text information to Facebook were more likely to exhibit online trolling behavior compared to those posting text information outside of Facebook. However, this was not found for online trolling victimization. A further assessment noted that 203 (71.2%) showed at least 1 instance of online trolling behavior within the last week. On the other hand, 211 (74.0%) experienced at least 1 instance of online trolling victimization in the last week. These ratios are indeed quite high. In terms of the average scores of university students in questions on online trolling behavior, the top five online trolling behaviors recognized by university students in the last week were: “I like to offer useful advice on the Internet so that others will agree with me,” “I want to leave texts on interactive networks to elicit discussion of everyone,” “I like to be a spiritual teacher to other people online, but I do not enact these words or methods in real life,” “I want to provocatively make people online laugh out loud with more shocking methods,” and “When making comments online, I want inexperienced users or novices to believe in my words.” These all came under evocative trolling. Furthermore, in terms of the factor averages of university students in online trolling behavior, evocative trolling was the type most recognized by university students as online trolling behavior, followed by malicious trolling, obstruction trolling, and finally pathological trolling. In terms of the average scores of university students in questions on online trolling victimization, the top five online trolling victimization behaviors recognized by university students in the last week were: “I often receive untrue information on the Internet,” “I often laugh out loud at various provocative statements on the Internet,” “It is easy for me to believe that other people make truthful statements online,” “I like to accept other people’s spiritual and life guidance online, but I cannot achieve these words or methods in the real world,” and “When playing online games, other people obstruct me in reaching the game’s objectives.” The first two were dissemination victimization, the next two were identity victimization, and the last one was obstruction victimization. Finally, in terms of the factor averages of university students in online trolling victimization, identity victimization was the type most experienced by university students, followed by dissemination victimization, malicious victimization, and obstruction victimization. 4.2. Correlation analysis and hierarchical regression analysis According to Table 1, there is a significant correlation among the subscales and totals of online trolling behavior and online trolling victimization, social extraversion, sense of inferiority, neurotic, and depression. First, the subscales and totals of online trolling behavior present a significantly positive correlation with that of online trolling victimization. Moreover, there is a significantly positive correlation between social extraversion and the totals of obstruction trolling, evocative trolling, and online trolling behavior, but it does not bear a relation to the subscales and totals of online trolling victimization Second, sense of inferiority has a significantly positive relation with the subscales and totals of online trolling behavior and with the totals of malicious victimization, identity victimization, obstruction victimization, and online trolling victimization. Third, there is a significantly positive correlation between neurotic and the subscales and totals of online trolling behavior and with the totals of identity victimization and online trolling victimization. Finally, depression bears a significantly positive relation to the subscales and totals of online trolling behavior and online trolling victimization. The four two-layered hierarchical regressions were used to explore the role of such variables as gender, grade, websites with frequently-posted written information and personal traits in the prediction of malicious trolling, obstruction trolling, evocative trolling, and pathological trolling, as is shown in Table 2. All four kinds of hierarchical regression analysis adopted the same procedure, the four models were established respectively, and the three variables (gender, grade, and the websites with frequentlyposted written information) were put into use for the first time. The four predictive variables, including social extraversion, sense of inferiority, neurotic, and depression, were then put in the second model. The results show that social extraversion is a significant predictive variable for malicious trolling, obstruction trolling, evocative trolling, and pathological trolling, while depression significantly positively predicts evocative trolling and pathological trolling. The four two-layered hierarchical regressions were used to explore the roles of variables like gender, grade, websites with frequently-posted written information and personal traits in the prediction of malicious victimization, identity victimization, obstruction victimization, and disseminated vulnerability, as is shown in Table 3. As for the procedure of hierarchical regression analysis in this part, the above method was adopted to put in the variables so as to form a model. According to the results, social extraversion is a significant predictive variable for malicious victimization. At the same time, sense of inferiority significantly predicts identity victimization and obstruction victimization in a positive way, while depression significantly predicts malicious victimization in a positive way. Two two-layered hierarchical regressions were used to explore the roles of variables such as gender, grade, websites with frequently-posted written information and personal traits in the prediction of online trolling behavior and online trolling victimization, as is shown in Table 4. As for the procedure of hierarchical regression analysis in this part, the above method was adopted to put in the variables so as to form a model. According to the results, sense of inferiority is a significant predictive variable for online trolling behavior and online trolling victimization. Moreover, social extraversion and depression significantly predict online trolling. 4

p < .01;

**

M is average mean; SD is standard deviation. *p < .05;

1 1 .603*** .534*** .629*** .899*** .666*** .414*** .438*** .306*** .572*** .109 .172** .125* .210***

2.43 1.97 3.69 1.15 9.24 2.77 3.84 2.20 3.75 12.56 1.10 8.15 7.86 6.15

SD

7.10 3.65 4.75 2.18 14.69 6.37 5.35 3.85 4.80 16.80 4.91 4.67 4.72 4.98

1Malicious trolling 2 Obstruction trolling 3 Evocative trolling 4Pathological trolling 5 Online trolling 6 Malicious victimization 7 Identity victimization 8 Obstruction victimization 9 Disseminated vulnerability 10 Online trolling victimization 11 Social extraversion 12 Sense of inferiority 13 Neurotic 14 Depression

M

***

5 p < .001.

1 .568*** .535*** .803*** .429*** .428*** .460*** .372*** .511*** .129* .180** .125* .199**

2

1 .471*** .793*** .437*** .527*** .445*** .458*** .566*** .153** .234*** .177** .278***

3

1 .738*** .425*** .424*** .353*** .340*** .475*** .069 .200** .217*** .242***

4

1 .633*** .540*** .523*** .439*** .657*** .145* .233*** .181** .277***

5

1 .613*** .636*** .475*** .856*** .086 .151* .089 .177**

6

1 .572*** .610*** .856*** .003 .316*** .297*** .287***

7

Table 1 The Zero-Order Correlation of Online Trolling, Online Trolling Victimization, and Psychological Trait of College Students (N = 285).

1 .491*** .793*** .040 .152* .044 .137*

8

1 .773*** .073 .113 .101 .163**

9

1 .064 .225*** .167** .236***

10

1 −.299*** −.096 −.164**

11

1 .557*** .567***

12

1 .607***

13

1

14

F.-Y. Hong, K.-T. Cheng

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Table 2 Predictive analysis of the subscales of online trolling of college students (N = 285). Malicious trolling Mode 1

Mode 2

Obstruction trolling

Evocative trolling

Pathological trolling

Mode 1

Mode 1

Mode 1

Mode 2

Mode 2

Mode 2

Predictors

β

t

β

t

β

t

β

t

β

t

β

t

β

t

β

t

Gender Year Website more often used to post text information Social extraversion Sense of inferiority Neurotic Depressive F value R2 △F value △R2

−.15 −.02 −.11

−2.39* −.25 −1.85

−.13 −.06 −.08

−2.14* −1.02 −1.45

−.13 .04 −.03

−2.07* .61 −.44

−.11 −.01 .00

−1.80 −.21 −.01

−.07 .10 −.01

−1.17 1.54 −.14

−.05 .03 .03

−.77 .50 .52

−.04 .07 .07

−.66 1.10 1.10

−.02 .02 .10

−.37 .38 1.67

.17 .17 −.05 .15 4.34** 0.10 5.09** 0.07

2.68** 2.23* −.63 1.93

.19 .18 −.05 .15 4.11*** 0.10 5.50*** 0.07

3.01** 2.39* −.71 1.88

.13 .10 .08 .16 4.19*** 0.08 6.36*** 0.08

2.14* 1.35 1.08 2.00*

*

p < .05;

**

p < .01;

***

3.17* 0.03 3.17* 0.02

2.22 0.02 2.22 0.02

.24 3.88*** .21 2.75** −.05 −.61 .22 2.87** 6.69*** 0.15 10.13*** 0.15

1.85 0.02 1.85 0.02

1.20 0.01 1.20 0.01

p < .001.

Table 3 Predictive analysis of the subscales of online trolling victimization of college students (N = 285). Malicious victimization

Identity victimization

Obstruction victimization

Disseminated victimization

Mode1

Mode 1

Mode 1

Mode 1

Mode 2

Mode 2

Predictors

β

t

β

t

β

t

Gender Year Website more often used to post text information Social extraversion Sense of inferiority Neurotic Depressive F value R2 △F value △R2

−.04 .07 .07

−.66 1.10 1.10

−.02 .02 .10

−.37 .38 1.67

−.01 .08 −.10

−.08 1.30 −1.73

.13 .10 .08 .16 4.19*** 0.10 6.36*** 0.08

2.14* 1.35 1.08 2.00*

*

p < .05;

**

p < .01;

***

1.20 0.01 1.20 0.01

1.65 0.02 1.65 0.02

Mode 2

β

t

β

t

.00 .04 −.08

−.04 .65 −1.47

−.15 .02 −.05

−2.39 .25 −.84

.08 .22 .12 .09 6.50*** 0.14 9.97*** 0.12

1.27 2.99** 1.55 1.12 2.56 0.03 2.56 0.03

*

β

t

−.14 −.01 −.04

−2.31 −.14 −.74

.08 .19 −.13 .10 2.72* 0.07 2.79* 0.04

1.19 2.45* −1.61 1.24

*

Mode 2

β

t

β

t

−.03 .04 −.06

−.43 .62 −.95

−.01 .01 −.04

−.17 .12 −.59

.11 .08 −.02 .14 1.63 0.04 2.42* 0.03

1.70 1.00 −.27 1.73

0.58 0.01 0.58 0.01

p < .001.

Table 4 Predictive analysis of online trolling and online trolling victimization of college students (N = 285). Online trolling behavior Model 1

*

Online trolling victimization Model 2

Model 1

Model 2

Predictors

β

t

β

t

β

t

β

t

Gender Year Website more often used to post text information Social extraversion Sense of inferiority Neurotic Depressive F value R2 △F value △R2

−.13 .04 −.05

−2.15* .69 −.88

−.11 −.02 −.02 .22 .21 −.04 .21 6.73*** .15 9.64*** .12

−1.83 −.34 −.30 3.68*** 2.81** −.53 2.68**

−.10 .06 −.09

−1.59 .88 −1.44

−.09 .01 −.06 .12 .20 −.03 .15 4.26*** .10 5.64*** .07

−1.42 .22 −1.11 1.92 2.55* −.40 1.85

p < .05;

**

p < .01;

***

2.54 .03 2.54 .03

p < .001.

6

2.27 .02 2.27 .02

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5. Discussion Compared to past studies on online trolling behavior, which generally did not analyze the types and frequencies of online trolling, or the current conditions of online trolling victimization, the present study’s goal is to identify the online trolling behavior and online trolling victimization conditions that may be observed by university students in online text posting and game text interactions. This study compiled the multifaceted online trolling behavior scale and online trolling victimization scale, which were not only effectively applied to university students, but may also serve as a reference for future research. This study further explored personality trait factors that may affect online trolling behavior and online trolling victimization. Results of this study provide important preliminary data on how university students’ personality traits affect online trolling behavior and online trolling victimization, thus providing important information on expanding our understanding of personal traits in university students leading to online trolling behavior and online trolling victimization. The results herein showed that in the previous week, at least 70% of university students had at least 1 instance of online trolling behavior and 1 instance of online trolling victimization, which are higher ratios than in past studies (Rice, 2013). At the same time, university students perceived more online trolling behavior on Facebook, but no significant difference in the perception of online trolling victimization. A possible reason may be that Facebook has broader functions in transmitting information by status updates, group messages, and gaming interaction, with a higher level of visibility, and so online trolls may be more willing to engage in online trolling on Facebook. Indeed, any online platform that allows group interaction, posting, and chatting may present more online trolling behavior, such as in Facebook, Twitter, Whatsapp, and Instagram (Ansong et al., 2013). However, as perception of online trolling victimization may be due to a lack of social cues such as facial expression and tone, it is not possible to effectively perceive the veracity of information; moreover, most people may hope that everyone can conform to online usage norms and trust that other people should abide by them, or be punished for their violations (Bicchieri, 2006, p. 16). Thus, university students generally paid greater attention to text and information shared by others, and most believed that such information was reliable, hence resulting in their victimization. In terms of the types of online trolling behavior and online trolling victimization perceived by university students, the most common types were evocative trolling behavior and identity trolling victimization. Evocative trolling behavior may be hypocritical and may be a concealment of one’s intent to sabotage, to gain a sense of satisfaction from the pain of others, or to evoke agreement, discussion, and resonance in others to prove and satisfy one’s desire to control others through power. Going even further may make endangering suggestions that result in negative effects in others. Similarly, evocative victimization refers to when an individual believes in an online discussion to induce negative emotions or to shake personal thoughts, resulting in victimization. Further analysis showed that compared to other types of online trolling behavior and victimization, which had concealed intents and unpredictable effects on victims, evocative trolling and identity victimization encompassed fraudulent psychological games in which the troll attempted, desired, and expected the victims to fall into their trap. These common evocative trolling behaviors reflected that the troll wanted to control the victim’s thoughts, emotions, and actions. The online platforms and online games were only media, and the text information was just a tool. This fact deserves attention. It should be noted that the college students were invited to self-state any possible online trolling behavior and online trolling victimization in the past week to explore the relationship among the perceived online trolling behavior of college students, the meaning of online trolling behavior victimization, and personal traits. Moreover, this study analyzed different kinds of online trolling behaviors and classified them and connected them with personal traits. Aside from understanding online trolling behavior and the possible types of online trolling victimization, this study found that the kinds of personal psychological traits could be the hazard factors that influence the online trolling behavior of college students and their online trolling victimization. According to the results of this study, we first note that social extraversion is a significant predictive variable for four kinds of online trolling: malicious trolling, obstruction trolling, evocative trolling, and pathological trolling. The possible reason for the results is that highly extraverted people are straightforward and more social and have a strong desire to communicate with peers, and hence they expand and deepen online trolling by posting information on the Internet and interacting through written information in games. It is obvious that highly extraverted college students still show the trait of attracting attention and interacting with others, which contributes to the diversity of their online trolling behavior. Second, this study’s results show that sense of inferiority significantly predicts malicious trolling, obstruction trolling, and evocative trolling in a positive way, indicating that those with sense of inferiority may exhibit such trolling behavior as harassing or threatening others, obstructing others from using the Internet, shaking others’ stances, and triggering others’ echo and discussion to take the opportunity at self approval and to test their status on the Internet. However, they also need to face the possible danger of others’ negative feedback in a failure. Finally, this study shows that depression significantly predicts evocative trolling and pathological trolling, possibly because depressed people have less intimacy and less personal control over conversation in daily interaction (Nezlek et al., 2000), are socially isolated (Joiner, 1997), and have deficits in terms of social skills (Segrin, 2000). As a result, they may deliver their personal morbidity and negative thoughts and feelings through online trolling as a form of extending their depressed emotions and ideas. Different kinds of online trolling victimization may present different personal traits. According to the results of this study, social extraversion is a significant predictive variable for malicious victimization. Sense of inferiority significantly predicts identity victimization and obstruction victimization in a positive way, while depression significantly predicts malicious victimization in a positive way. First, those with a high score in social extraversion are thought to be good at communicating with others, have a wide social network, often express ideas or share information on the Internet, and attract the attention of others, thus becoming more vulnerable to malicious trolling. Second, those with a stronger sense of inferiority are more likely to show less self-confidence, understate their abilities, and be more vulnerable to the influence of others, thus having a greater likelihood of taking opinions on the Internet 7

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seriously, becoming undetermined about their ideas, stances, and objectives, and then suffering from negative emotions. Finally, depression significantly predicts malicious victimization in a positive way, which may indicate that vulnerability to malicious trolling in games, provocation, attacks, tricks, deception, harassment, or threats from other netizens may cause a high level of depression for the victims. This is a problem worth further attention. Findings from this study’s hierarchical regression analysis may have significant practical significance for social workers, counselors, and administrative personnel and teachers at schools. Those with high online trolling behavior tend to have personality traits, including extraversion, emotional instability, and a less healthy psychology. It was also perceived that more online trolling victims were inclined toward emotionally unstable personality traits. Specifically, extraversion, sense of inferiority, and depression may be seen as personality risk factors that may develop into online trolling behavior, and sense of inferiority may be seen as a personality risk factor that may lead to online trolling victimization. Results of the present study showed that sense of inferiority was a personality variable that could effectively explain both online trolling behavior and online trolling victimization, meaning that those who scored high on sense of inferiority (inferiority feeling) may use online trolling behavior to compensate for their low selfconfidence. Particularly, when a victim falls into a carefully planned trolling game, those who also had a higher sense of inferiority score meant that they were more likely to be affected by others and therefore also likely to become victims in online trolling. In addition, social extraversion can significantly positively predict online trolling behavior. Thus, an effective identification of potential online trolls includes those with higher social extraversion personality traits who are more likely to actively seek social interaction online so that they may appear in different networks, while simultaneously using the online anonymous environment to present different online actions from those in real life, which leads to aggravate online trolling behavior. Finally, those with high depressive personality traits may also become high-risk for online trolling behavior. Since depressive university students are more likely to be brooding, often pessimistic, they may use anonymity and absent contact methods online to engage in online trolling behavior to reduce their stress in life. Since the results of this study were preliminary, we still hope that the online trolling behavior scale and online trolling victimization scale can be used as effective tools for screening online trolls and victims, which can also be utilized as a basis for future research. However, some limitations may affect this study. First, the online trolling behavior scale and online trolling victimization scale compiled in this study are not sufficient for clinical diagnosis of antisocial behavior. However, based on the scales compiled in this study, future studies can further explore the motivation of online trolls, the possible effects of online trolling behavior on victims, and the response strategies of online trolling victims to online trolling behavior. Moreover, if this study is correct in its deduction that what evocative trolling behavior reflects is that the perpetrator wants to control the thoughts, emotions, and behaviors of the victim, then what thoughts, emotions, and behaviors of the victim do the perpetrators most want to control? Second, because the study used university students who reflected on their perceived online trolling behavior or encountered online trolling victimization in the past week, it may have been that there were unknown validity problems in the real context of online interactions. In other words, did only one type of online trolling behavior and online trolling victimization occur? Or did they appear together? What were the extents of online trolling behavior and online trolling victimization that occurred? These problems require observation or experimentation in future studies for analysis in the real and natural environments of online interaction, in order to understand the actual prevalence of online trolling behavior and online trolling victimization, as well as how online trolling behavior actually affects students. Finally, since only students of three universities in Taiwan were analyzed, the generalizability of the results require more samples for verification. References Adrian, A., 2010. Beyond griefing: virtual crime. Comput. Law Secur. Rev. 26, 640–648. Ang, R.P., Tan, K., Mansor, A.T., 2011. Normative beliefs about aggression as a mediator of narcissistic exploitativeness and cyberbullying. J. Interpersonal Violence 26, 2619–2634. http://dx.doi.org/10.1177/0886260510388286. PMID:21156699. Ansong, E.D., Takyi, T., Damoah, D., Ampomah, E.A., Larkotey, W., 2013. Internet trolling in ghana. Int. J. Emerging Sci. Eng. 2 (1), 42–43. Balka, E. 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