Running head: CYBERBULLYING AND SOCIAL INFORMATION PROCESSING Cyberbullying in Elementary School: The Role of Hostile Attribution Bias in Children’s Social Information Processing

As children gain access to electronic communication devices at increasingly younger ages, bullying is no longer restricted to the traditional “schoolyard” setting. The present study investigates a) the prevalence of cyberbullying in a sample of fourth and fifth graders and b) the role of hostile attribution bias (HAB) in children’s interpretations of ambiguous cyber provocation scenarios and involvement in traditional and cyber bullying and victimization. Fourth and fifth graders completed self-report measures that assessed their past involvement in traditional and cyber bullying and victimization, as well as HAB. It was found that children are involved in cyberbullying as early as elementary school, and that while involvement in traditional bullying predicts being a cyber bullying, both traditional victimization and HAB index predicts being a cyber victim. These data suggest that there is overlap between traditional and cyber bullies and victims; however, the results also demonstrate the increased inherent ambiguity of the cyber environment. These results have important implications for understanding the potentially harmful role of social cognitive deficits in children and it is therefore important for future researchers to continue to investigate traditional and cyber bullying through a social information processing framework. CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 3 Cyberbullying in Elementary School: The Role of Hostile Attribution Biases in Children’s Social Information Processing In light of numerous publicized cases of bully-related suicides in the past several years, increased efforts have been made to identify and understand the factors that may predict children’s involvement in bullying. Additionally, researchers and policymakers have focused much attention on creating effective interventions aimed at educating children about the harmful consequences of involvement in bullying. Nonetheless, bullying continues to occur both in and outside of school, leading many children and adolescents to experience long-term pain and emotional distress (Beran & Li, 2007; Toblin, Schwartz, Gorman & Abou-ezzeddine, 2005). Moreover, rapid technological advances have resulted in increasingly younger age groups gaining widespread access to electronic communication devices. As early as elementary school, children average 46 minutes of computer use in a typical day. Additionally, the percentage of 8 to 10 year olds who own a cell phone has grown from 21% in 2004 to 31% in 2009 (Rideout, Foehr, & Roberts, 2010). Despite the potential merits of children using such forms of technology, these new modes of communication have created new venues for negative social interactions that were previously restricted to traditional social contexts (i.e., face-to-face communication). More specifically, the types of bullying that previously exclusively occurred in a traditional “schoolyard” setting are materializing in cyberspace. In light of the transition of bullying from traditional to cyber environments, the present study investigates how a typical predictor of traditional aggression and victimization, the hostile attribution bias, may similarly predict children’s involvement in cyberbullying. By evaluating children’s social information processing, I CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 4 hope to identify the extent to which attributional biases are related to children’s involvement in cyberbullying. Children’s Technology Use From 1999 to 2009, 8to 18-year-olds have increased their average daily amount of media use from 6 hours and 19 minutes to 7 hours and 38 minutes. Additionally, significantly more children and young adults have their own electronic devices (e.g., cell phones, laptops, iPods) than in 2004 (Rideout, Foehr, & Roberts, 2010). These statistics alone demonstrate the growing role that electronic media play in children’s lives and indicate that these numbers will likely only continue to increase as time goes on and reliance on quick and efficient communication grows. More specifically, the most popular activities among 8to 18-year-olds are social networking both online and through text messaging, behaviors that often go unmonitored by parents or school officials. With a 17% jump in laptop ownership among this same age group (from 12% in 2004 to 29% in 2009), it is hardly surprising that children and adolescents’ online activity typically occurs within private confines and therefore may be of a socially inappropriate nature (Rideout, Foeher, & Roberts, 2010). As Internet processing speed continues to quicken and social networking sites, such as Facebook and MySpace, become increasingly accessible to younger age groups, more and more children have come to incorporate electronic communication into their daily social lives. What is Cyberbullying? Due to the aforementioned changes in early technology access and use in the past five years, increased emphasis has been placed on understanding children and adolescents’ bullying behavior within a cyber context. Although the exact definition of CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 5 cyberbullying slightly varies across studies and specific researchers, it has typically been defined as repeated acts of aggression that are carried out through an electronic medium and are characterized by an imbalance of power between bully and victim (Dooley, Pyzalski, & Cross, 2009; Li, 2007; Li, 2010). Additionally, this aggression typically involves ignoring others (e.g., not responding to a message), spreading rumors, and/or disrespectful name-calling (Patchin & Hinduja, 2006). Recent research has indicated that a significant percentage of students across elementary, middle, and high school have been involved in cyberbullying to some extent, whether it be as victims, bullies, or both. Although relatively early studies of cyberbullying found that approximately 20% of middle school students were involved in some degree of electronic bullying (Kowalski & Limber, 2007; Li, 2007), more recent reports of cyberbullying frequencies in middle school students indicate that up to 50% have been victims alone and approximately 33% have bullied others online (Mishna, Cook, Gadalla, Dcciuk & Solomon, 2010). These high rates of cyberbullying are a cause for alarm and necessitate additional research to explore both why and how children become involved in cyberbullying. Furthermore, because the abovementioned frequencies relate specifically to students in middle school, it remains unclear if elementary students’ involvement in cyberbullying mirrors that of early adolescents. Although several studies have included participants in elementary school, their data have rarely been analyzed separately; rather, these studies combine results across ages, making it difficult to draw conclusions about elementary school students in particular. In light of the sparse research examining cyberbullying in elementary school students, the majority CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 6 of research reviewed here concerns older age groups, specifically middle and high school students. Cyberbullying Versus Traditional Bullying Although there is evidence that individuals involved in traditional bullying as victims, bullies, or both are often also involved in cyberbullying (Li, 2007), several significant differences exist between these two forms of bullying. Through comparisons of cyberbullying and traditional bullying, researchers have demonstrated disparity between the two, both in terms of the frequency of occurrence and the nature of bullying behavior itself. In general, cyberbullying occurs less frequently (although nonetheless appreciably) than traditional bullying (Slonje & Smith, 2008; Smith et al., 2008). Additionally, whereas traditional bullying typically occurs in school, cyberbullying is more likely to take place outside of school, especially given the restrictions on electronic device use in the classroom (Smith et al., 2008). Because cyberbullying occurs electronically, children are afforded anonymity that is missing in face-to-face interactions. By hiding behind a computer or phone screen, children feel more comfortable communicating in ways that are interpreted as inappropriate in alternate contexts. Victims often do not know the identity of their cyberbullies; the invisibility of perpetrators may therefore make cyber victims feel significantly more threatened and paranoid than they would be with knowledge of the sender (Kowalski & Limber, 2007; Suler, 2004). In addition to inducing some degree of dissociative anonymity (separation of online actions from in-person identity) in users, electronic communication takes place in a venue where victim and perpetrator lack access to the social and contextual cues typically present in face-to-face interactions. Therefore, CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 7 bullies may not perceive their cyber communications to be hurtful, whereas victims may interpret hostility in the absence of additional contextual cues (e.g., tone of voice) (Kowalski & Limber, 2007). Without the different types of feedback that exist in physically proximate interactions, such as facial expressions, extent of eye contact, and body language, individuals interacting in cyberspace experience increased disinhibition of language and actions and greater difficulty making accurate attributions of intent (Suler, 2004). The electronic nature of cyberbullying also limits the specific forms of aggression exhibited in this context. Extensive research has identified several different forms of traditional aggression, of which relational and physical aggression are most commonly cited (Crick, Ostrov & Werner, 2006). Physical aggression, as implied by its title, is generally overt and involves the use or threat of physical damage in order to induce harm. Alternatively, and more commonly seen in girls, relational aggression entails the use or threat of relationship damage in order to induce harm. Rather than kicking or punching, agents of relational aggression engage in rumor-spreading, social exclusion, and/or social threats (e.g., “I won’t be your friend if...) to aggress against others. Because victims and bullies are not physically proximate in the cyberworld, the majority of cyber-aggression involves specific forms of relational aggression. Alternatively, physical aggression in cyberspace is limited solely to threats of harm. Research has also indicated that cyberbullying causes increased harm to victims given its somewhat inescapable nature. Whereas traditional bullying is typically restricted to the confines of the school, cyberbullying can occur across multiple environments. Although limitations on cell phone and computer use in schools help to prevent instances CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 8 of cyberbullying in academic settings, cybervictims’ homes often transform from safe havens to new sites for harassment (Dempsey, Kowalski, Nichols & Storch, 2009; Slonje & Smith, 2008). Unfortunately, victims of cyberbullying exhibit reluctance to report instances of harassment to both school officials and parents. Children often fear a loss of Internet and phone privileges at home and do not interpret the school administration as having jurisdiction over extra-institutional instances of bullying (Slonje & Smith, 2008). Focus group studies have also provided personal insight from students themselves regarding how cyberbullying is unique in its impact on their social and emotional functioning. Echoing many findings of previous empirical studies on cyberbullying, middle and high school students emphasized their reluctance to report incidents due to fear of privilege loss at home and reported an increased frequency of cyberbullying outside of the school environment (Agaston, Kowalski & Limber, 2007). Although they proposed some potential strategies for responding to cyberbullying (e.g., blocking sender), they did not acknowledge the option of asking an authority to take down an offensive website or speaking up as a bystander to cyberbullying. Therefore, it seems that the non-confrontational nature of cyberbullying, unlike traditional bullying, leaves victims feeling a lack of efficacy in preventing future instances of harassment. Because cyberbullying appears to be a distinct construct, it is important to understand its unique impact on children. Although there is some degree of overlap between children who are involved in traditional bullying and cyberbullying, such dual involvement is by no means the case across all individuals. It is possible that children who are neither involved in relational nor physical aggression in the traditional sense are chronic victims or bullies in the cyber world (Dempsey, Kowalski, Nichols & Storch, CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 9 2009). The anonymity and lack of contextual cues in cyber interactions may make individuals more likely to interpret harmless online interactions as intentionally hostile. Therefore, more research is necessary to examine how these features unique to cyberbullying affect children’s social cognitions. Types of Cyberbullying Although the present study examines social cognitive variables associated with cyberbullying at a more general level, cyberbullying, like traditional bullying, takes a variety of forms both in terms of the physical mechanism used by perpetrators and the content of the specific affront. Many of the tactics used in cyberbullying exemplify its uniqueness as a type of bullying, and are thus helpful in understanding children’s interpretations of online/mobile social interactions. Despite the numerous forms of modern technology that allow for instant communication among children, most research on cyberbullying to date has identified the Internet and mobile phones as being the most common domains for such activity (Katzer, Detchenhauser & Belschak, 2009; Slonje & Smith, 2008). More specifically, cyberbullying tends to take place in chatrooms, over email, and through text messaging. As these technologies continue to develop innovative capacities that allow fast-paced interactions and the exchange of more than just text content (e.g., pictures and video), children are becoming equipped with a wide variety of options for both positive and negative forms of social communication. It is therefore hardly surprising that these forms of electronic media serve as venues for new forms of bullying. Across several studies, researchers have converged upon seven typical types of cyberbullying: harassment, denigration, masquerading, CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 10 outing, trickery, exclusion, and cyberstalking (Dempsey, Sulkowski, Nichols & Storch, 2009; Katzer, Detchenhauser & Belschak, 2009; Mishna, Cook, Gadalla, Daciuk & Solomon, 2010; Willard, 2004). Although all of these categories fall under the umbrella of cyberbullying, each one exhibits a distinct definition and purpose. Harassment, as the term typically connotes, involves the repeated sending of offensive or hurtful messages across any form of electronic media (Li, 2010; Willard, 2004). Similarly, cyberbullies who engage in denigration publically send or post cruel assertions (which are not necessarily true) about another peer. Some research has demonstrated that victims of online bullying often know the bully; however, it is not rare for cyberbullies to engage in masquerading, or the impersonation of someone else. Because the online environment facilitates attempts at anonymity, masquerading provides children an opportunity to aggress upon their peers without concern for eventual identification (Suler, 2004). Masquerading also allows for online forms of relational aggression; a bully can pretend to be someone else and then send/post information to destroy a person’s reputation or social relationships (Willard, 2004). In the same vein of reputation damage, outing refers to the online and public disclosure of someone’s private information or pictures. Given the permanent nature of the Internet and phone messages, outing in the context of cyberbullying may exacerbate the victim’s feelings of shame and powerlessness. A similar mechanism for cyberbullying is trickery, or misleading someone into divulging personal and/or embarrassing secrets about him/herself (Willard, 2004). As in the case of outing, acts of trickery often result in hurtful posts or messages that are impossible for the victim to remove. Another form of cyberbullying, perhaps most parallel to traditional types of bullying, is exclusion. CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 11 Exclusion generally involves deliberately leaving someone out of an online or mobile group, such that the person is not awarded access to the social cyber-interactions of his/her peers (Willard, 2004). The final form of cyberbullying, cyberstalking, is arguably the most harmful and thereby most concerning method of victimization. Characterized by recurring harassment and attacks, cyberstalking is used by bullies to instigate fear and intimidation in their victims (Willard, 2004). In the case of cross-gender cyber interactions, cyberstalking has been found to occasionally take the form of sexual harassment. More specifically, especially among older adolescents, girls have been found more likely than boys to receive unsolicited sexual pictures or messages requesting them to engage in some sort of sexual act for a boy online (Mishna, Cook, Gadalla, Daciuk & Solomon, 2010). Cyberstalking, in addition to the six other aforementioned methods of cyberbullying, consistently demonstrates its potential to provoke intense hurt and shame in the victims of such acts. Although typically observed in middle and high school students, with growing numbers of elementary school students gaining access to electronic communication, cyberstalking may begin to emerge at even younger ages. In order to effectively understand reasons for young children’s involvement in cyberbullying both as victims and perpetrators, we must be mindful of the specific practices most frequently used to carry out aggressive exploits. Characteristics of Cyber Bullies and Victims Much research has also been dedicated to identifying personal characteristics of children and adolescents who are typically involved in cyberbullying. Although the present study specifically focuses on the role of social information processing variables CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 12 as they relate to cyberbullying, it is important to understand how and why particular deficits in social cognition may uniquely relate to individuals involved in cyberbullying as bullies, victims, or both. In movies and television, bullies are often characterized as big, violent boys who pick on their weaker and less popular classmates. In actuality, bullies are rarely immediately recognizable, and their motives for engaging in aggressive behavior are more complex than simply being driven by anger. Across multiple studies, several key variables have been identified as consistent predictors of cyberbullying, the first of which concerns students’ perceptions of the moral acceptability of engaging in cyberbullying. Perhaps not surprisingly, youth in elementary, middle, and high school who express moral approval of cyberbullying are more likely to be cyberbullies themselves (Pornari & Wood, 2010; Williams & Guerra, 2007). Students’ perceptions of their school environments also serve a predictive value, such that youth who view their school climates positively are less likely to participate in cyberbullying. Similarly, youth who perceive themselves to have a supportive and trusting peer network report lower levels of involvement in cyberbullying (Williams & Guerra, 2007). Victims are also characterized by a set of distinct variables, both psychosocial and behavioral in nature. In general, victims are often low in popularity and self-concept, making them appear as easy targets (Katzer, Detchenhauer & Belschak, 2009). Furthermore, high levels of characterological self-blame (blaming own personality for harm) have been found closely associated with a victim status. It seems that individuals who hold stable negative views of themselves perceive such traits as unchangeable, and are thus less likely to attempt to alter their own behaviors. Victims are also more likely CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 13 than uninvolved children to exhibit interpretive biases in social cognition, such that they assume hostile intent in other people’s actions when it may actually be absent or inadvertent (Pornari & Wood, 2010). Finally, research has demonstrated slight differences in victim responses to bullying across gender, such that victimized boys exhibit high levels of revenge-seeking tendencies whereas victimized girls display depressive attributional styles (Shelley & Craig, 2010). In addition to studying the characteristics of cyberbullies and victims, researchers have also directed attention towards a third category of cyber roles: bully-victims. As the title implies, bully-victims are involved in cyberbullying both as the perpetrator and the victim, making them a particularly interesting group of youth to study. Children and adolescents who fall into this category are typically high frequency and high expertise Internet users who lack adequate parental monitoring (Ybarra & Mitchell, 2004). Like victim-only children, they also tend to display significant interpretive biases (Bailey & Ostrov, 2008). Such biases lead bully-victims to often engage in a cyclic pattern of cyberaggression; because they often misinterpret hostile intent of others, they are more likely to retaliate by cyberbullying the perceived perpetrator or other children (Pornari & Wood, 2010). Interpretive biases in social information processing, therefore, can set in motion a potentially destructive chain of events for cyberbullies and victims. Social Cognitive Theories of Aggression To better understand the motivations driving participation in childhood cyberbullying, attention must be focused on identifying the underlying cognitive mechanisms involved in such aggression. Much of the relevant research to date focuses on how certain children’s social information processing is prone to cognitive biases that CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 14 ultimately result in inaccurate interpretive patterns and maladaptive behavior (Bailey & Ostrov, 2008; Camodeca & Goossens, 2005; Camodeca, Goossens, Schuengel & Terwogt, 2003; Crain, Finch & Foster, 2005; Dodge & Frame, 1982; Dodge, Murphy & Buchsbaum, 1984; Joscelyne & Holttum, 2006; Shelley & Craig, 2010; Toblin, Schwartz, Gorman & Abou-ezzeddine, 2005). Although social cognitive theories of childhood aggression are widespread, they largely focus on traditional forms of aggressive behavior and have not yet addressed how new social environments (e.g., electronic media) may alter the nature of social cognition. Here, I review previous research exploring how social information processing relates to traditional aggression and examine the extant, though minimal, literature investigating similar theories in the context of traditional and cyber bullying. Social Information Processing Model. Extensive research has explored how children and adolescents’ social information processing (SIP) styles affect their cognitions and, in turn, their behavioral responses to perceived provocation. Dodge (1986) conceptualized a model that outlines five separate stages of social information processing in children which, when completed skillfully, results in appropriate behavioral responses. Alternatively, deficits in one or more stages of processing often result in maladaptive responses, such as aggression. Dodge and Crick (1994) later reformulated this model to include six distinct stages involved in social information processing. In stage one, children encode social cues in the environment, often using cognitive heuristics (e.g., schemata) to efficiently keep track of appropriate information. Following encoding, children develop causal attributions and interpret the intention behind a given action. The third stage involves the determination of goals, followed by stage four, a CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 15 mental search for potential responses to a specific provocation or interaction. In the final stages, children select the response they perceive as most appropriate (stage five) and then finally, in stage six, enact the selected behavior. Dodge’s social information processing model provides an effective framework for understanding the cognitive mechanisms underlying aggressive behavior. Children who, for example, fail to accurately encode and interpret the existing social cues are likely to select inappropriate behavioral responses, such as aggression (Dodge & Crick, 1990). Consequently, much of the existing research on social information processing as it relates to aggression has focused on identifying the cognitive mechanisms that differentiate aggressive children from nonaggressive children. Early research concerned specifically with aggression in young boys has demonstrated that an association exists between aggression and attribution biases, such that aggressive elementary school boys, as compared to nonaggressive elementary school boys, overattribute hostile intent to peers (Dodge & Frame, 1982). Additionally, this deficit in intention reading exists only when the subject interprets himself, rather than a second peer, as the target of victimization. Therefore, it appears that cognitive biases in attribution are stronger when individuals interpret a personal threat. Further research has replicated these findings across both male and female elementary school students, indicating that the association between attribution style and aggression holds across both boys and girls. Dodge (1986) found support for the SIP model in his study of social information processing patterns of severely aggressive second through fourth graders. Not only were aggressive children more likely than nonaggressive children to assume that peers did not want to play with them, but they also CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 16 expressed lower levels of support for competent solutions to relieve feelings of social discomfort. Aggressive children also failed to acknowledge the ineffectiveness of their proposed solutions, indicating that in addition to struggling with general social information processing, aggressive children lack awareness of their own social incompetence. Similarly, socially deviant children have been found to frequently mislabel prosocial and accidental intentions as being hostile, leading them to favor aggressive responses to provocation scenarios (Dodge, Murphy & Buchsbaum, 1984). It seems, then, that children who lack accuracy in intention-cue reading are predisposed to higher levels of aggression. Previous research has also examined how different stages of the SIP model may be uniquely associated with specific subtypes of aggression, namely proactive and reactive aggression. Whereas proactive aggression has been characterized as instrumental and deliberate in nature, reactive aggression is retaliatory and defensive, and usually accompanied by frustration and/or anger (Camodeca, Goossens, Schuengel & Meerum, 2003; Camodeca & Goossens, 2005; Crick & Dodge, 1994; Crick & Dodge, 1996). Given the distinction between these two forms of aggression, it has been proposed that each subtype reflects deficits in distinct stages of the social information processing model. Multiple studies have demonstrated that reactively aggressive children exhibit biases in the interpretive stage of processing, such that they often attribute hostile intent to peers in ambiguous provocation scenarios, frequently resulting in retaliatory acts of aggression. Alternatively, proactively aggressive children show evidence of distorted response decision processes, viewing instrumentally aggressive behavior as effective and positive means to an end. Proactive aggression, unlike reactive aggression, is CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 17 characterized by a goal-oriented motivation in which aggression is interpreted as the most valuable instrument (Crick & Dodge, 1994; Crick & Dodge, 1996; Pornari & Wood, 2010). Moreover, proactive aggression is associated with bullies, whereas reactive aggression has been found to be more characteristic of victims (Toblin, Schwartz, Gorman & Abou-ezzeddine, 2005). Essentially, bullies may be driven by a deliberate intention to engage in aggression to fulfill a goal, whereas victims are prone to interpretations of hostile intent and, in turn, retaliatory aggression. More recent research has challenged such a polarized distinction between reactive and proactive aggression as they relate to the social information processing model, demonstrating that there may indeed be more overlap in the social cognitive processing of proactive and reactive aggressors than previously conceived (Camodeca & Goossens, 2005). Although proactive aggression was found to be uniquely associated with bullying, reactive aggression was linked with both bullying and victimization, indicating that bullies may too show deficits in their interpretive patterns. Moreover, both bullies and victims exhibited processing deficits in all stages of the SIP model, indicating that this framework describes a relatively circular process where each step is interrelated. Early steps of interpretation influence the later behaviors, and the outcome influences future social interpretations; the same pattern continues across future social interactions. These findings offer a more cohesive structure for understanding social information processing as it relates to aggression, illustrating that perhaps different subtypes of aggression and specific stages of SIP cannot be studied in isolation. Hostile Attribution Bias. In identifying the specific deficits associated with each stage of Dodge’s social information processing model, researchers have pointed to a CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 18 hostile attribution bias (HAB) as an interpretive bias that leads to the frequent misinterpretation of social cues. Across multiple studies, hostile attribution bias has been defined as a tendency to attribute hostile intent to others’ unintentional negative actions/interactions due to deficits in the second (interpretive) stage of social information processing (Camodeca, Goossens, Schuengel & Terwogt, 2003; Crick & Dodge, 1996; Katsurada & Sugawara, 1998). Past research has revealed that victims of aggression tend to exhibit hostile attribution biases, although there remains uncertainty as to the direction of this relationship (Pornari & Wood, 2010). Hostile attribution bias is also a particularly strong predictor of reactive aggression, such that individuals who inaccurately attribute hostile intent to social cues are more likely to interpret threat and react aggressively (Bailey & Ostrov, 2008). Even in preadolescents, hostile attribution bias partially mediates the association between victimization and engagement in relational aggression (Yeung & Leadbeater, 2007), and therefore this cognitive bias appears to be an important mechanism driving involvement in aggression. Additional research has specified the contexts in which HAB is more or less strong by taking into account the significance of relationship type in peer provocations (Peets, 2007). Hostile attribution biases have been identified as a cognitive deficit that skew social interpretations in many aggressive children; however, these biases actually demonstrate remarkable flexibility, such that children generally show greater hostile attributions towards enemies than other peers, especially friends. It has also been proposed that, in general, the association between hostile attribution bias and aggression is significantly stronger for traditionally aggressive boys than relationally aggressive girls. When girls were presented with ambiguous relational provocation scenarios and CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 19 asked to report intent attributions, there was not a strong relationship between HAB and peer-nominated reports of relationally aggressive behavior (Crain, Finch & Foster, 2005). Taken together, these findings provide evidence for the potential context-specificity of the SIP model; certain types of aggressive scenarios demonstrate significantly stronger associations with hostile attribution biases and other cognitive mechanisms than others. Furthermore, when examining HAB in the context of cyberbullying it is important to acknowledge the unique characteristics of the bullying environment and tactics used by perpetrators. Social Cognitive Theories of Bullying Despite the breadth of research examining social information processing as it applies to childhood aggression, less attention has been directed at understanding how a similar social cognitive perspective provides insight into the mechanisms driving different forms of bullying. Because bullying involves repeated instances of aggressive behavior, it is important to identify the social cognitive deficits that may characterize both bullies and victims. As early as elementary school, children demonstrate an ability to develop their own attributional accounts of why bullying occurs, using both characterological and behavioral explanations (Joscelyne & Holttum, 2006). They are able to attribute bullies’ actions to both internal stable traits (e.g., The bully isn’t smart) and behaviors (e.g., The bully hit the boy because the boy was calling him names). However, school age children involved in bullying as either victims, bullies, or both exhibit more deficits than uninvolved children in understanding the actions and intentions of their peers’ social behavior and are more likely to interpret threats in social situations (Camodeca, Goossens, Schuengel, & Terwogt, 2003). More specifically, those involved CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 20 as both bullies and victims tend to show deficits in the second stage of social information processing (interpretation) as well as the fifth stage (response selection), suggesting that perpetrators and victims of bullying are overwhelmingly characterized by deficits in social cognition abilities. Therefore, I seek to use a social information processing framework to further investigate the relationship between children’s attributional tendencies and interpretations of ambiguous social interactions in a cyber context. In doing so, I hope to better understand how children’s social cognitions may relate to their involvement in cyberbullying. Social Cognitive Theories of Cyberaggression Of particular interest to the present study is how theories of HAB and Dodge’s social information processing model operate in the relatively novel cyber world. To date, limited research has explored the role of social cognitive factors associated with individuals involved in cyberbullying. Furthermore, the extant findings largely concern middle and high school populations, rather than elementary school students, thus providing an incomplete window into the phenomena of interest. In fact, to my knowledge there has only been one study to date that has examined HAB in relation to cyber aggression. Focusing specifically on the relationship between cognitive mechanisms in both traditional and cyber aggression, researchers found that both cyber victimization and traditional victimization are associated with hostile attribution bias, indicating that victims of aggression may hold negative and skewed views of their social environment and interactions (Pornari & Wood, 2010). It is therefore important for future research to elucidate the social cognitive mechanisms underlying children who are involved in cyberbullying, both as victims and aggressors. CYBERBULLYING AND SOCIAL INFORMATION PROCESSING 21