Cyberbullying: Exploring Components of Offending in the Lens of the Social Learning Theory

Introduction

As technology continues to advance in the 21st century, adolescents have become susceptible to the potential dangers that the Internet poses. Cross et al. (2015), stated that 98% of adolescents aged 12-14 years old have accessed the internet and have electronic devices such as cell phones and computers.

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It is suggested that the more time adolescents spend online in chat rooms, emails, and other social networking sites the more likely they are to be victims of various online crimes such as cyberbullying (Holt et al., 2015). To better assess the victims and their needs in cyberbullying crimes, first, it’s important to understand the foundations of why people take part in cyberbullying behavior. The development of computer-mediated communication has contributed to the change in how adolescents communicate and engage with one and other in the online world (Holt et al., 2015). Cyberbullying is defined as any intentional, aggressive behavior performed through electronic means (Holt et al., 2015). This form of cyber deviance often occurs repeatedly, rarely is it ever a one-time offence. Cyberbullying can be accomplished by sending or posting hurtful and degrading messages via email, instant message, and other social media outlets. Facebook, Instagram, and Twitter are all common social media platforms where cyberbullying can take place. (Holt et al., 2015).

The act of engaging in this type of deviance is considered aggressive behavior where the offender poses both social and emotional harm on a victim, which could result in victims experiencing embarrassment, shame, anger, frustration, and depression (Holt et al., 2015). In the United States alone, cyberbullying has become a major epidemic and is becoming more prominent in our society now more than ever. According to the National Crime Victimization Survey-Supplemental Survey regarding bullying and cyberbullying, it was discovered that 6 percent of students ages 12-18 were cyberbullied during the 2007-2008 calendar year (Holt et al., 2015). The use of handles by offenders, also known as nicknames, makes it extremely difficult to investigate these types of offences, therefore the offender often goes unnoticed (Holt et al., 2015). A lack of funding and skill poses problems for law enforcers when it comes to investigating cybercrime incidents that are reported to them directly. In terms of prevalence, Ybarra and Mitchel (as cited in Holt et al., 2015), conducted research which concluded that 18 percent of their youth sample had engaged in cyberbullying behavior within a year period. It is predicted that this number in the U.S. is steadily increasing due to exposure of technology at earlier ages. When considering these statistics, it’s important to understand that these are only representations of incidents that individuals report directly to law enforcers.

Cyberbullying is heavily underreported a lot of the time because individuals often feel embarrassed or feel their claims won’t be heard or addressed by law enforcement (Holt et al., 2015). Research provided by Hinduja and Patchin (2013), suggested that their youth sample that engaged in cyberbullying offending was significant in terms of their likelihood to involve themselves in deviant behavior. The sample, which consisted roughly 4,500 adolescents, found that almost 19.5% of them at some point have engaged in some form of online bullying (Holt et al., 2015). It is important to understand that people’s actions that occur in cyberspace, whether it’s cyberbullying or another form of online deviance, leave harmful consequences in the real world. Extreme cases could potentially lead to anxiety/depression and thoughts of suicide (Holt et al., 2015). In order to explore the victimization aspect of cyberbullying crimes, it’s crucial to understand the motives behind the offender’s actions. Analyzing the issues of cyberbullying in the eyes of the offender is critical in comprehending what exactly drives them to take part in this behavior, to begin with. In order to properly explore, the social learning theory is the most appropriate way to understanding the presented ideas. The purpose of this study is to focus mainly on adolescents and examine factors in cyberbullying through the offender’s eyes, and to explore the relationships this topic has through the lens of Akers (1999) social learning theory.

Presentation of Theory In 1998, Ronald Akers established what we commonly refer to today as the social learning theory. This theory is an expansion of Edwin Sutherland’s differential association theory (Siegel & Worrall, 2014). Sutherland argued that deviant behavior that may be committed by a criminal is learned in a process with differential interactions with others (Holt et al., 2015). Adding on, the most important aspect he demonstrated is that interactions are formed within intimate personal groups such as close peers and family. The social learning theory correlates best to the offending side of cyberbullying. Prior research has suggested that this theory has been successful in understanding why individuals participate in a number of deviant activities (Miller & Morris, 2014). Similarly, Akers (1999), expanded on Sutherland’s theory by focusing in depth on the learning process by adopting the idea of differential association. The social learning theory also suggests that people learn attitudes, behaviors, and values that could potentially lead to prosocial and criminal behavior (Siegel & Worrall, 2014). When evaluating individuals through this theory, it is suggested that criminal behavior is learned both in nonsocial settings and through social interactions. Within social interactions, the behavior presented by another person may be reinforced and may be deemed as acceptable to some individuals (Miller & Morris, 2014). According to Akers (1999), there are four components that make up the social learning theory. The components include differential associations, definitions, differential reinforcement, and imitation (Akers, 1999).

Differential associations suggest that individuals who associate with deviant peers often involve themselves in deviant behavior, predominately both in direct and indirect interactions. In other words, individuals could be social contacts that are either direct or indirect that could be present in the real world or in cyberspace (Miller & Morris, 2014). Definitions refer to an individual’s own values and beliefs, especially when it comes to weighing what is and is not acceptable behavior. Based on the study by Miller and Morris (2014), being exposed to such definitions influences a person’s likelihood in whether or not they engage in deviant behavior based on their personal definitions of what they consider to be deviant or not in cyberspace. Differential reinforcement, according to Miller and Morris (2014) and Akers (1999), suggests that there is a balance of rewards and punishments which contributes to whether or not an individual partakes in offending (Miller & Morris, 2014). Positive reinforcements are considered to be a form of approval from certain behaviors that individuals model in society. These reinforcements could come from parents, close friends and other individuals that have close relations to each other (Miller & Morris, 2014). They further explain that positive reinforcements could potentially increase the probability of an event occurring. If for example, an adolescents friend showed approval in cyberbullying behavior and deems it is okay, they themselves may be more likely to take part in cyberbullying. Contrary, those who discipline undesirable behaviors could potentially decrease an act of deviance altogether. (Miller & Morris, 2014).

The last element of the social learning theory is imitation. Imitation refers to the process of learning behavior through a process called socialization (Miller & Morris 2014). It is demonstrated that peers are often able to share beliefs, attitudes, and knowledge that may potentially influence or persuade an individual to partake in the similar deviant behaviors as their peers (Miller & Morris, 2014). Potential sources that could contribute to imitation could be family, friends, and media where individuals are able to admire and imitate learned behaviors. These four components are key to the subsequential process that makes up this theory. It is suggested that deviant behavior can be studied with the framework of these principles. The social learning theory is an effective way of understanding why some individuals are involved in cyberbullying offending. Literature Review In the research provided by Li et al. (2016), the purpose of their study was to examine more in-depth the relationship between low self-control and the social learning variables, in order to further predict cyberbullying behavior. According to Li et al. (2016), they conducted an experimental study in which data was collected from a self-report survey that was administered to 518 middle and high school students in the rural area of Kentucky in May of 2008, (Li et al., 2016). The independent variable was measured using two of the four elements of the social learning theory, differential association and definitions (Li et al., 2016).

The dependent variable in this study was the act of cyberbullying offending which assessed how often the children posted threatening or harmful messages about another person (Li et al., 2016). Regarding the social learning theory, the findings concluded that associating with deviant peers statistically demonstrated a positive correlation (Li et al., 2016). They also concluded that this theory emphasized support on cyberbullying offending. Additionally, the results showed that predictors of cyberbullying could be assessed successfully with the principles of the social learning theory. Li et al. (2016) concluded that their findings help make sense of the relationship between cyberbullying, social learning, and self-control. The purpose of Hinduja and Patchin (2013) study was to look further into adolescent’s peers, parents, and educators as well as explore the influence they have on cyberbullying behaviors. They conducted an experimental study, the data was collected from a survey that was distributed in the spring of 2010 to a random sample of adolescent students that ranged from the sixth through twelfth grade. The final sample consisted of 4,441 students from one of the largest school districts within the United States.

The independent variable in this study was considered peer involvement. The adolescents were asked to recall whether or not their friends in specific have ever bullied anybody. The dependent variable was considered cyberbullying offending. The measure included a variety of different behaviors that ranged from minor to more serious offences. Their research findings indicated that adolescences who partake in cyberbullying behaviors are often influenced by peers. Their research relates to three elements of the theory; differential association, differential reinforcement, and imitation. Hinduja and Patchin (2013) found evidence that suggested students who reported that their friends have bullied others before were more likely themselves to become a cyberbully. They also generated the conclusion that parents and educators who provide sanctions as a result of cyberbullying behavior also play an important role when it comes to preventing this behavior. This is because adolescents who believed they would get in trouble for their actions were less likely to engage in the behavior altogether (Hinduja & Patchin, 2013).

The purpose of the research provided by Miller and Morris (2014) was to examine the differential influence of face-to-face and virtual peers in order to predict digital and traditional offending among 454 college students. They examined the students through the lens of the social learning theory in order to examine some of the direct and indirect differences in offending (Miller and Morris, 2014). Their main focus was to see if the theory operates accordingly when virtual peers are modeled rather than traditional peers (Miller & Morris, 2014). In order to test their ideas, they conducted an experimental study in which data was collected from self-administered surveys. The surveys were completed by undergraduate college students from a southern university in the spring of 2010. The independent variable in this study was peer involvement and informal sanctions which were measured using different scales that assessed all elements of the social learning theory. The dependent variable was considered traditional deviance and offending as well as cyber deviance (e.g., digital piracy) (Miller & Morris, 2014). They reported in their finding that younger individuals were more likely to express involvement in deviant behaviors both online and in the real world when analyzed with the elements of the social learning theory. Their findings also suggested that males in this study were influenced more by virtual peer associations rather than females (Miller & Morris, 2014).

Conclusion

The three articles mentioned above had similar findings in regards to two of the four components of the social learning theory, differential association and definitions. The studies by Li et al. (2016) and Hinduja and Patchin (2013) suggested that individuals who associate with deviant peers that model antisocial behavior are considerably more likely to take part in cyberbullying offending. Miller and Morris (2014) focused on both online and traditional offending and examined direct and indirect disparities within the social learning principles through virtual and traditional peers. They focused their research on those who take part in digital piracy, but still concluded similar findings in comparison to the other researchers. It can be implied that further research needs to be done in order to better assess the other two components of the theory, differential reinforcement and imitation in relation to the topic of cyberbullying. The focus of this paper was to further examine the offending side of cyberbullying deviance in adolescents through Akers (1999) social learning theory. In the selected research studies discussed above, they generally agree that the social learning theory emphasized support on cyberbullying offending when assessed through this theory’s principles. The four elements of this theory received statistical support when the data was analyzed. Differential association and definitions had the most support when exploring cyberbullying offending.

These studies provided statistical evidence that the social learning theory is useful in analyzing the offenders that partake in cyberbullying deviance. This theory is successful in understanding the learning process behind individuals who engage in these types of behavior. The elements of this theory can be used to justify and understand the behavior and motives behind a cyberbullying offender. In general, cyberbullying, as opposed to other types of crimes, is highly underreported. It is important to understand why offenders engage in cyberbullying behavior. to begin with. It’s also crucial to shine a light on some policies and implications that have been established to help the victims who have been affected by these types of online deviances. In order to reduce and help those who have been victimized, many actions have been implemented in order to protect those affected and help educate the public. Unfortunately, there is a lack of federal legislation regarding cyberbullying and traditional bullying here in the United States (Holt et al., 2015). As of now, there are 49 states in the U.S, including the District of Columbia, that require schools to have a set policy regarding bullying incidents (Holt et al., 2015).

Cyberbullying language is only specified in policies implemented in 17 states, while 47 states use language that addresses electronic harassment. In response to bullying behaviors, only 12 states in the United States, including the District of Columbia, give criminal sanctions to individuals who participate in bullying behaviors (Holt et al., 2015). As mentioned in the introduction, cyberbullying can be extremely tricky to pinpoint due to the uncertainty of a person’s true identity on the other side of the screen. Therefore, without accurate knowledge and certainty of someone’s true identity, it’s difficult to punish and hold individuals accountable. Even though our nation doesn’t have set laws to help protect those who are the unfortunate victims of cyberbullying, there are services and programs that are meant to help those who have been victimized and educate those who may not know much about the topic. In the United Kingdom, they implement a successful non-profit group that help assess the needs presented by the victims of cyber deviance who ultimately feel uncomfortable or embarrassed about reporting their incidence to the police (Holt et al., 2015). “Cybersmile” is an organization that was founded back in 2010. It is well known for educating and providing resources to the victims involved in cyberbullying incidences (Holt et al., 2015).

This organization also provides a helpline for the victims who were affected by online bullying and provide them with different resources and treatment options that are readably available to them (Holt et al., 2015). Furthermore, Cybersmile does an adequate job in spreading awareness to people within the community through their programs and fundraising events they host in order to build their organization (Holt et al., 2015). To help do this, Cybersmile has organized a day which is designated to spreading awareness about cyberbullying. In the United Kingdom, this day is known as Stop Cyberbullying Day (Holt et al., 2015). Due to rapidly evolving technology, it’s important that parents and schools have open and honest conversations with youth about the Internet. It’s beneficial to make children aware of some of the rights and wrongs in regards to their behaviors in the real world and how to implement the same principles online (Holt et al., 2015). To reiterate, it’s crucial to try and understand why individuals participate in cyberbullying behavior. In order to properly assess victim’s needs, cyberbullying offending can be successfully analyzed through the social learning theory in order to sufficiently understand offender’s motives.

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