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Cyberbullying Via Social Media Journal of School Violence, 14:11–29, 2015 Copyright © Taylor & Francis Group, LLC ISSN: 1538-8220 print/1538-8239 online DOI: 10.1080/15388220.2014.949377 Cyberbullying Via Social Media ELIZABETH WHITTAKER and ROBIN M. KOWALSKI Department of Psychology, Clemson University, Clemson, South Carolina, USA Recent years have witnessed a surge of research on cyberbullying. In this article, three studies examined prevalence rates of cyberbullying among college-age students, venues through which cyberbullying occurs, with a particular focus on social media, and perceptions of cyberbullying as a function of features of the tar- get (e.g., peer, celebrity, groups). Study 1 found texting and social media to be the most commonly used venues for cyberbullying victimization. Study 2 determined that features of the target of cyber aggressive comments influenced perceptions of cyberbullying. Online aggressive comments directed toward peers were perceived most negatively whereas those targeted toward random people known only online were evaluated least negatively. Using an inno- vative methodology for examining cyberbullying, Study 3 found that venue (e.g., Facebook, comments, forum posts) and features of the target influenced the nature of online exchanges. Implications for prevention and intervention are discussed. KEYWORDS cyberbullying, cyber aggression, peer aggression, school violence The last decade has witnessed a surge of research on cyberbullying, bullying that occurs through the use of electronic communication technologies, such as e-mail, instant messaging, social media, online gaming, or through digital messages or images sent to a cellular phone (Kowalski, Giumetti, Schroeder, & Lattanner, 2014; Kowalski, Limber, & Agatston, 2012; Patchin & Hinduja, 2012). Like traditional bullying, cyberbullying is an act of aggression intended to cause harm or distress, it has a repetitive quality (e.g., a single e-mail may be sent to hundreds of different individuals), and it occurs among individuals Received April 1, 2014; accepted July 23, 2014. Address correspondence to Robin M. Kowalski, PhD, Department of Psychology, Clemson University, Clemson, SC 29634, USA. E-mail: [email protected] 11 mailto:[email protected] mailto:[email protected] 12 E. Whittaker and R. M. Kowalski whose relationship is characterized by a power imbalance (Kowalski et al., 2012, 2014; Olweus, 1993; Patchin & Hinduja, 2012). Importantly, whereas with traditional bullying this power imbalance might reflect differences in physical strength or social status, with cyberbullying it might also reflect differences in technological expertise. Reported prevalence rates of cyberbullying are variable across stud- ies, depending on how cyberbullying is defined, the time parameter used to measure cyberbullying (e.g., has cyberbullying occurred in the last two months, last year, lifetime), the ages of the participants, the country of origin of the sample, and the response format used to classify involvement with cyberbullying (e.g., at least once, once or twice a week), to name a few (for a more complete discussion of conceptual and measurement issues related to cyberbullying, see Bauman, Cross, & Walker, 2012; Kowalski et al., 2014). Across most studies, prevalence rates range from 10% to 40% (e.g., Kowalski et al., 2014; Lenhart, 2010; O’Brennan, Bradshaw, & Sawyer, 2009). One variable affecting prevalence rates is the nature of the items used to assess cyberbullying. In some instances, participants are asked single-item questions determining whether they have ever been the victim or the per- petrator of cyberbullying. In other cases, participants are asked a series of questions determining whether they have been cyberbullied via a number of different venues (e.g., instant messaging, text messaging, e-mail, online gaming). Typically, prevalence estimates for cyberbullying are lower when single-item measures are used as opposed to when more specific items inquire about cyberbullying that occurs through particular venues (Kowalski et al., 2014; Menesini, Nocentini, & Calussi, 2011; Vaillancourt et al., 2010). Multiple items measures provide a more detailed portrait of the means by which cyberbullying occurs. Knowing that 19% of respondents report being victims of cyberbullying is not as informative as knowing the venues by which that cyberbullying has been perpetrated. These venues through which cyberbullying occurs reflect the technolo- gies most in use at the time. Thus, they change rapidly, with implications for prevention and intervention efforts that must keep up with the changes in technology. For example, Kowalski and Limber (2007) found instant mes- saging to be the most frequently used venue for cyberbullying reported by both victims and perpetrators. Katzer, Fetchenhauer, and Belschak (2009) observed chat rooms to be a common method of both peer-to-peer commu- nication and cyberbullying among middle and high school students. More recently, however, social media, such as Twitter and the like, appear to be emerging as popular sites for cyberbullying perpetration and victimization, in part a reflection of their increasing popularity. Focusing on the relation of social media to cyberbullying is an important goal in 2014. Thus, assessing the extent to which social media are emerging platforms for cyberbullying is one goal of the current series of studies. Cyberbullying 13 The conceptual and methodological issues surrounding research on cyberbullying have pointed to another deficiency in the literature. Much of the attention devoted to cyberbullying has focused primarily on peer-to- peer cyberbullying occurring through text messages, Facebook, and instant messages (Pyzalski, 2011, 2012). However, the relation between victim and perpetrator might not, in fact, be peer-to-peer. Indeed, in some instances, the relationship is not known as the victim and the perpetrator are unknown to each other. Pyzalski (2012) created a taxonomy to examine victim– perpetrator relationships in regards to cyberbullying. This taxonomy includes six categories: cyber aggression against peers (i.e., the victim and perpetrator are from the same group); cyber aggression against the vulnerable (i.e., the victims are “weaker” people, such as the homeless, alcoholics, etc., who may be unaware of the victimization); random cyber aggression (i.e., the victim is anonymous to the perpetrator); cyber aggression against groups (i.e., a group of people is victimized, such as an ethnic or religious group); cyber aggres- sion against celebrities (i.e., the victims are celebrities or otherwise famous); and cyber aggression against school staff (i.e., school staff/administrators are the targets of cyber aggression). Perceptions of the offensiveness of acts of cyber aggression and whether particular behaviors even constitute cyberbullying might be expected to vary as a function of the characteristics of the target, a second focus in the current series of studies. Third, to date, the majority of the research on cyberbullying has focused on youth in middle and high school to the virtual exclusion of another impor- tant segment of the school-age population—college students. One study found, however, that as many students reported that their first experience with cyberbullying occurred during college as occurred during middle school (Kowalski, Giumetti, Schroeder, & Reese, 2013; see also Cowie et al., 2013; Rafferty & Vander Ven, 2014). Given that cyberbullying can occur with any demographic, and with the increased use of apps, such as Yik Yak, currently in vogue on college campuses, this is a sample that warrants our attention. Yik Yak allows users to post short comments anonymously for anyone in that user’s vicinity (e.g., school) to view and vote on. In the current manuscript, three studies examine the prevalence rates of cyberbullying among college-age students, the venues through which cyberbullying occurs, and perceptions of cyberbullying as a function of features of the target (e.g., peer, celebrity, the vulnerable, groups). More specifically, Study 1 provides an overview of cyberbullying preva- lence rates and examines the correspondence between Internet tools and cyberbullying venues. Study 2 provides a novel conceptual approach to research cyberbullying using Pyzalski’s (2012) typology to examine instances of cyberbullying as a function of the nature of features of the tar- get. Important to Study 3 is an innovative methodology for examining cyberbullying using Salesforce’s Radian6 program, which is detailed later in this article. This methodology identifies cyberbullying behavior as it occurs online. 14 E. Whittaker and R. M. Kowalski STUDY 1 Study 1 was designed to explore prevalence rates of cyberbullying in addition to examining the correspondence between Internet use and cyberbullying venues. A specific focus was to determine the degree to which social media are popular platforms for cyberbullying perpetration and victim- ization among school-age youth. In addition, with an eye toward prevention and intervention, the study examined common responses to cyberbullying among targets and bystanders. Prevalence rates of cyberbullying were expected to mirror those observed with students in other age demographics. However, the venues through which cyberbullying occurs were expected to differ not only because of technological shifts but also because of the age of the participants. Participants were expected to not only spend more time on social media sites but also to report involvement in cyberbullying via these sites. Responses to cyberbullying were expected to be primarily indirect. Method PARTICIPANTS A total of 169 female and 75 male undergraduate students enrolled in an introductory psychology course (four did not identify their sex) participated. Participants’ ages ranged from 18 to 25 (M = 18.8, SD = 1.2). Eighty-four percent of the sample was White, with another 8.6% being African American. PROCEDURE After responding to demographic questions, participants completed an online survey examining their experiences with the Internet and with cyberbullying. Participants were asked how often they used the Internet on an average day (1 = 0 hours to 7 = >10 hours); how safe they felt using the Internet (1 = not at all safe to 5 = extremely safe); and how often they used a provided list of 14 electronic communication technologies (e.g., texting, Facebook, Twitter; 1 = never to 5 = frequently, at least once a day). In addition, questions adapted from the Olweus Bullying Questionnaire (Olweus, 1996/2004; see also Kowalski & Limber, 2007) were included to assess participants’ experiences with cyberbullying. Participants were first provided with the following definition of cyberbullying: When we say cyberbullied, we mean bullied through email, instant mes- saging, social media, in a chat room, on a website, in an online game, or through a text message sent to a cell phone. For example some- one who sends mean messages to another person in an email or posts negative comments or information about that person via social media, like Facebook, is cyberbullying. Cyberbullying 15 Then, they were asked the following questions: “How often have you been cyberbullied in the past year?”; “How often have you cyberbullied someone else in the past year?”; and “How often have you witnessed some- one else being cyberbullied in the past year?” Each of these questions was answered using a 5-point response scale (1 = I haven’t to 5 = several times a week). To gather information regarding the venues by which cyberbullying is most likely to occur, participants used this same 5-point response format to indicate the extent to which they had been cyberbullied via the same 14 elec- tronic communication technologies for which their overall use had been assessed earlier (e.g., texting, Facebook, Twitter). They were then asked to identify the perpetrator of the cyberbullying. Participants responded “yes” or “no” to each of the following choices: sibling, friend, another student at school, teacher, stranger/don’t know, or someone else. To gauge responses to cyberbullying victimization, participants gave yes/no responses to eight different possible responses that they offered in response to their own victimization (did nothing, reported the cyberbullying, asked the perpetrator to stop, cyberbullied back, made fun of the perpe- trator to other people, saved the evidence, blocked them on social media, responded in another way). Similar response options were provided, with the addition of “provided support,” for participants’ perceptions of the responses of others who had witnessed the participant’s victimization. Results Most participants reported using the Internet between 1 and 6 hours a day (1–2 hours: 18.9%; 3–4 hours: 45.1%; 5–6 hours: 25.8%). When using the Internet, over 77% reported that they felt moderately to very safe using the Internet. The average age at which participants began using social media was 13.3 (SD = 1.9). The most common technological tools reported by participants reflected high use of social media. The majority of participants (99.6%) reported using texting often or frequently, followed by e-mail (98.4%), Facebook (86.5%), YouTube (75.1%), Instagram (70.9%), and Twitter (69.4%). Contrary to previous research, participants infrequently stated that they used instant messaging (14.5%) or chat rooms (0.8%) often or frequently. The most fre- quent venues by which participants indicated they had been victimized were texting (56.8%), Twitter (45.5%), Facebook (38.6%), Instagram (13.7%), and YouTube (11.4%). Instant messaging (2.3%) and chat rooms (2.3%) were infrequent sources of cyberbullying victimization. Consistent with published research (e.g., Hinduja & Patchin, 2009; Kowalski & Limber, 2007), 18.2% of participants reported they had been a victim of cyberbullying at least once within the last year. Almost 12% indicated they had perpetrated cyberbullying at least once within the last 16 E. Whittaker and R. M. Kowalski year. Being a victim of cyberbullying was significantly related to being a perpetrator of cyberbullying (r = .54, p < .001). over 55% of participants stated they had witnessed cyberbullying at least once within the last year. in most cases, the perpetrator .001).="" over="" 55%="" of="" participants="" stated="" they="" had="" witnessed="" cyberbullying="" at="" least="" once="" within="" the="" last="" year.="" in="" most="" cases,="" the="">