The Oxymoronic Nature of Online Bullying
By Jonathan Scott
Abstract
Cyber Bullying (CB) is defined as the use of computers, mobile phones, and other devices to engage in deliberate, repeated, aggressive acts to harm others (Smith et al., 2008). CB is has many correlational causes like; violence tendency, disinhibition, past experiences, and anonymity all play a role in CB. The purposes of this study are to examine how adults react to CB and whether they become bullies in their reactions; as well as examine how they justify their own actions and therefore demonstrate the vicious circle that is online bullying.
Keywords: Cyber Bullying, disinhibition, anonymity, violence tendency, Self-justification
Introduction
There has and continues to be plenty of effort being allocated to the study of CB. Though traditional bullying isn’t a new problem, online bullying is newish and continues to grow as fast as the internet and social media does. More and more people are connecting to one and other giving voices and audiences to anyone with a Twitter, Facebook or Instagram account; Meaning that as a society we are increasingly able to connect in unprecedented ways. An unfortunate side effect of this connection is disagreement and bullying, which is often facilitated by anonymity and distance; because of this people feel they are free to say and do whatever they want without repercussions.
Literature review
2.1. Violence Tendency
The problem is especially bad in teenagers, in 2015 a Turkish study looked at the correlation between violence tendency and CB in adolescents (Sari, Serkan Volkan. Camadan, Fatih. 2015). They did this because of a rapid rise in 15-24 year olds internet and mobile phone use in several developing nations in the past 12 months (Sari, Serkan Volkan. Camadan, Fatih. 2015). “Given that these environments provide individuals with the opportunity of expressing their thoughts and feelings freely, negative thoughts and feelings might be part of interaction as well as positive ones” (Sari, Serkan Volkan. Camadan, Fatih. 2015). The ease at which the children can share has also facilitated the aggression in how they express themselves online, thus spawning the ripe environment for CB through insults, humiliation and abuse (Sari, Serkan Volkan. Camadan, Fatih. 2015). The aim of their research was to look at the correlation of violence tendency and CB as well as to see if violence tendency can predict CB behavior (Sari, Serkan Volkan. Camadan, Fatih. 2015). They used a “Revised Cyber Bullying Inventory (RCBI) and Violence Tendency Scale (VTS) to measure 286, 15-18-year-old high school students. Over the course of the six month study, Sari & Camadan found that violence tendency and cyber bullying had a positive correlation. They also found that violence tendency is a valid predictor of cyber bullying (2015). The results also indicated that after enough time the cyber bullies were eventually exposed to bullying themselves (Sari, Serkan Volkan. Camadan, Fatih. 2015), illustrating the vicious circle of bullying online.
2.2. Disinhibition
A similar study of 146 Greek Jr high students looked at other variables that affect cyber bullying frequency. Variables like internet use and disinhibition, psychopathic traits, sensation seeking, social skills and peer relations and empathy (Antoniadou, Nafsika. Kokkinos, Constantinos M. Markos, Angelos. 2016). They tested about 5 hypotheses with the aforementioned variables being tied together in each, for example H3 “Students participating in cyber (especially bullies and bully-victims) and traditional bullying/victimization will use the Internet more frequently and dangerously than those uninvolved” (Antoniadou, Nafsika. Kokkinos, Constantinos M. Markos, Angelos. 2016). They found a significant positive correlation between victimization and bullying along with strong associations to disinhibition and psychopathic traits (Antoniadou, Nafsika. Kokkinos, Constantinos M. Markos, Angelos. 2016). These results are significant because the they illustrate a key difference between traditional and cyber bullying, with cyber bullying there is an increased disinhibition that comes with online anonymity.
3.3. Anonymity
Christopher P. Barlett looked at frequency of cyber bullying and its association to anonymity. He felt that because of de-individualization there would be more CB as opposed to traditional bullying (2015). Barlett does point out that, it is not uncommon for the victim to know the bully, it is just more common online that the bully is anonymous (2015). Barlett looked at 181 undergrad students and studied how instant messaging (IM) and anonymity are related to CB. As with the previous studies their hypothesis was supported and shows that anonymity is another strong factor related to CB online.
2.4. Adults that were victims of childhood bullying
In 2012, Randy A Sansone and Justin S Leung looked to see if they could find a relationship between aggressive behavior as an adult and past victimization of a bully. Of the 342 participants 42% had been bullied growing up. Aggression was measured by behavioral displays as in punching a wall or shoving a partner or spouse. They found a strong correlation between being bullied and aggression as an adult as opposed to not experiencing bullying as a child (Sansone, Randy A. Leung, Justin S 2012). Again showing the vicious circle, that even the victims of CB will trend more towards the more aggressive side of behavior,
2.5. Reactions to Bullying
How do teens respond to bullying? A study by Bolin Cao and Wan-Ying Lin looked at reactions to bullying, they wanted to examine how teens would react to witnessing bullying on social networking sites (SNS) (2015). Bolin Cao and Wan-Ying Lin were looking for what types of behaviors the teens would exhibit, prosocial (helping) antisocial (joining in on bullying) and ignoring. They found that 16.6% of their sample (N=622) had been cyber bullied in the past and more showed prosocial as opposed to anti-social behavior (2015). Results also concluded that if the teen had been cyber bullied in the past they were more likely to have an antisocial reaction, however girls were more likely to be more prosocial in their reactions to witnessing CB on SNS (Cao, Bolin. Lin, Wan-Ying. 2015).
Overview of the Current Study
The purpose of this study is to look at how Adults react to witnessing CB. Previous literature has shown that CB in teenagers eventually becomes full circle where the bully’s end up being bullied. CB is facilitated by disinhibition and anonymity, furthermore it would be interesting to see how adults would react when witnessing others being bullied in an online environment. It would also be interesting to see if they feel self-justified in their actions towards the bully. More than likely they will adjust their own moral definition of bullying to justify their own bullying (Robson and Witenburg (2013). Take for example the recent United states presidential election. During the campaign democrats along with the mostly liberal media accused Donald Trump of being a Bully. The accusation is interesting because after Donald Trump won, democratic party supporters became bullies to those who supported Donald Trump. This demonstrates the oxymoronic nature of bullying where, the bullies, were bullied, by the people calling them bullies. For example, if you were to post a pro Donald Trump Facebook status, you might have been called an “idiot”, “ill-informed” or worse, by the very same people calling Trump a bully. I use the Election as a back drop, because calling someone an “idiot” (or worse) is intended to hurt and therefor is by definition bullying. I will test, at what point will a witness to bullying go from prosocial protection of a victim, to actually becoming a cyber bully themselves? It is hypothesized that because of disinhibitions association with anonymity online, that if a cyber bully is vulgar enough to a victim, that an innocent anonymous witness will become a cyber bully in attempt to protect the victim and feel justification in their own actions.
Method
Procedure is to recruit 120 mature college or graduate school’s student to get a sample of adults ranging 24-30 years of age, then randomly assigned (30 males and 30 female) per condition. In exchange for participating in the study, students will be given an extra 4 percent in a first year course. Participants will sign up online to ensure age and gender criteria is met as well as to book the appointment for the study. At that point student’s information will be coded to remove identity from each subject so proper data collection after completion will be unbiased. The students will also receive a user name that is A. their own (control) or B. unique (test group) and un identifiable to them.
Materials
The only materials needed for the study will be a computer and mouse. However, they will need to complete a group problem solving game followed by post-test questionnaires.
Group problem solving game (Custom). Students will enter the lab and be told they are working with 2 other students online to solve a problem or achieve a goal. The other 2 students will be confederates and the participant will only see the others name or user name. The game will last 30 mins and in that time 3 levels of testing will be occur.
Aggressive behavior questionnaire: The ABQ was used by Sansone, and Leung to measure aggression levels in people that have past experiences with bullies. Questions samples include “Punched a wall when angry?” and “Beat up anyone such that they required
medical attention?” (2012) responses to the questions are Y/N.
Online Use Scale (custom): Questions were designed to gage how much someone uses online social networking sites i.e. Facebook, Twitter, Instagram. Questions will include but aren’t limited to “on a given day how often would you check your Facebook?”. Next asking “How often do you post on your Facebook? Followed by “how often do you comment on another-persons posts on Facebook?” All the questions will use a Likert design (1 very little-very often 7), and all the other SNS will have the same questions asked to fully gage the amount of online activity.
Cyber Bullying Inventory: was developed by Erdur-Baker and consisted of two parallel forms; that measure both bullying and cyber victimization. Cyber bully form had 16 questions and cyber victim form had 18 questions (Çi dem Topcu, Özgür Erdur-Baker 2010).
Moral Disengagement scale: Developed by Albert Bandera the questionnaire is designed to examine “(a) the behavior, (b) the agent’s responsibility, (c) the target of the behavior, and/or (d) the outcomes. Reframing the behavior is accomplished through moral just-ifications, euphemistic labeling, and/or advantageous com-parisons, which enable the individual to view their immoral behavior as ultimately moral or benign” (Runions & Bak. 2015).
Procedure
The goal is to find out, if at extreme levels, will a participant’s anonymity affect how they react to a bully. During registration for the study participants will complete the Online Use Scale. Then to do this, deception is key so upon arrival participants will be told that they are there to study online team work, and that we are looking to see how people from different university’s in Canada will work together to solve a common problem that should take about 30 mins. Because SNS are fast and fluid, I will use a within subject’s design, because I am interested in their immediate reactions when situations change. In condition 1, participants will use their-own name and our confederates will have made up common names like, Steve or Kelly. In Condition 2, the participants will have their usernames they acquired during registration, and the confederates will also have user names like, turkyfarm73 or pop-n-lock$. During the problem solving game there will be 3 conversational levels tested; Level 1, Confederates are nice and polite and work with participant to solve the problem (Control). Level 2, Confederate 1 makes a suggestion and confederate 2 says that “that is a dumb idea” or I can’t believe you suggested that that’s silly” (moderate bullying). Level 3, Confederate 1 suggests an idea and confederate 2 says “OMG that was the dumbest thing I have ever heard I can’t believe they let some idiot like you into school SERIOUSLY” or “WTF are you RETARDED that will never F*CKING work (extreme bullying). Each level of testing will last 10 mins and will be counter balanced and sequenced in a Latin square design, to ensure randomization (Lewandowski, Jr. Ciarocco, Strohmetz (2016). Participants responses to the bullying and non-bullying will be categorized in prosocial, anti-social and aggressive groups. Then checked to see if they meet clearly defined measures of bullying for example; did the participant resort to name calling “no you’re the ididot, so shut the F up” (aggressive) or “you can’t talk to people like that” (Prosocial) or “can we just focus on the task please” (anti-social/ignoring). After the participant responds, it will be key to examine how they responded, what level they responded at and whether or not they continued to respond to the bully. After word the participants will complete the ABQ, CBI and MDS, then upon completion participants will be debriefed.
References
Antoniadou, Nafsika. Kokkinos, Constantinos M. Markos, Angelos. (2016). Possible common
correlates between bullying and cyber-bullying among adolescents. Democritus University of Thrace, Greece.
Barlett, Christopher P. (2015) Anonymously Hurting Others Online:The Effect of Anonymity on
Cyberbullying Frequency. Psychology of Popular Media Culture. American Psychological Association 2015, Vol. 4, No. 2, 70–79.
Cao, Bolin. Lin, Wan-Ying. (2015). How do victims react to cyberbullying on social networking
sites? The influence of previous cyberbullying victimization experiences. Department of
Media and Communication, City University of Hong Kong, Hong Kong
Çi dem Topcua, .zgür Erdur-Bakera. (2010) The Revised Cyber Bullying Inventory (RCBI):
validity and reliability studies a Middle East Technical University. Ankara, Turkey.
Procedia Social and Behavioral Sciences 5 (2010) 660–664
Lewandowski, Jr.Gary W. Ciarocco, Natalie J. Strohmetz, David B. (2016) Within-Subjects
Design. Discovering the Scientist Within: Research methods in psychology. 327-328. Worth Publishers
Robson, Clair. Witenburg, Rivka T. (2013). The Influence of Moral Disengagement, Morally
Based Self-Esteem, Age, and Gender on Traditional Bullying and Cyberbullying. Journal of School Violence, 12:211–231, 2013 LLC online DOI: 10.1080/15388220.2012.762921
Runions, Kevin. Bak, Michal. Online Moral Disengagement, Cyberbullying, and Cyber-
Aggression. CYBERPSYCHOLOGY, BEHAVIOR, AND SOCIAL NETWORKING Volume 18, Number 7, 2015 DOI: 10.1089/cyber.2014.0670
Sari, Serkan Volkan. Camadan, Fatih (2015). The new face of violence tendency: Cyber
bullying perpetrators and their victims. Department of Psychological Counseling and Guidance, Faculty of Education. Recep Tayyip Erdogan University, Rize, Turkey.
Sansone, Randy. Leung, Justin. (2012). Having been bullied in childhood: Relationship to
aggressive behaviour in adulthood. International Journal of Social Psychiatry 59(8) 824-826.
Smith, P.K. Mahdavi, Jess. Fisher, Sonja. Carvalho, Manuel. Russell, Shanette. Tippett, Neil.
(2008). Cyber-bullying Journal of Child Psychology and Psychiatry, 49, pp. 376-385
http://dx.doi.org.ezproxy.macewan.ca/10.1111/j.1469-7610.2007.01846.x