Thesis (Ph. D.)--University of North Texas, Dec., 2009. / Title from title page display. Includes bibliographical references.

Thesis (M. S.)--Literature, Communication, and Culture, Georgia Institute of Technology, 2009. / Committee Chair: Celia Pearce; Committee Member: Carl DiSalvo; Committee Member: Fox Harrell; Committee Member: Jay Bolter.

Thesis (M.Ed.)--Victoria University of Wellington, 2009. / Includes bibliographical references.

Thesis (M.A.)--York University, 2008. Graduate Programme in Psychology. / Typescript. Includes bibliographical references (leaves 53-60). Also available on the Internet. MODE OF ACCESS via web browser by entering the following URL: http://gateway.proquest.com/openurl?url_ver=Z39.88-2004&res_dat=xri:pqdiss&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&rft_dat=xri:pqdiss:MR51515

Technology continues to evolve quickly and is dramatically changing the behaviors of online users. Social networking sites, while offering users interactive online spaces to socialize with their friends and family, are also a breeding ground for various undesirable online behaviors, such as cyberbullying. Cyberbullying on social networking sites (SNS bullying) has emerged as a societal challenge in recent years. The prevalence and adverse consequences of SNS bullying have been extensively reported in the mass media and drawn increasing attention from government agencies, parents, and the academic community. The research on SNS bullying is broad, and little effort has been devoted to consolidating its findings. Furthermore, scant attention has been paid to understanding the role technological factors play in the development of SNS bullying.. Accordingly, this dissertation proposes two main research objectives to advance the scientific understanding of SNS bullying. It seeks to (1) summarize the research status of SNS bullying and (2) examine the role of technological factors in SNS bullying among perpetrators and aggressive bystanders. Three essays are included. In Essay 1, I summarize the current knowledge on SNS bullying through a literature review and analysis. Drawing on the general aggression model, I propose a classification framework to classify the factors affecting SNS bullying. The literature review and analysis outline the patterns of research on SNS bullying and identify future research directions. In Essay 2, I examine the effects of technological factors on SNS bullying perpetration. Drawing on crime opportunity theory and affordance theory, I propose a research model to examine the drivers of SNS bullying perpetration and test how SNS affordances influence the evaluation of SNS environments for perpetration using an online survey. The results suggest that SNS affordances are salient enablers that afford SNS bullying perpetration. In Essay 3, I examine the effects of technological factors on bystanders' aggressive responses to SNS bullying. Drawing on moral disengagement theory, I develop a research model to investigate the effects of beliefs about SNS use and moral disengagement mechanisms on bystanders' aggressive responses to SNS bullying using a focus group discussion and a scenario-based survey. The results suggest that moral disengagement mechanisms are significant social cognitive processes bystanders use to rationalize their aggressive responses toward victims.. This dissertation offers important implications for research and practice. Theoretically, it contributes to the information systems (IS) literature by examining an emerging societal challenge associated with the undesirable use of information technology. It also adds to the growing body of research on SNS bullying by integrating knowledge from multiple disciplines, and demonstrates that technological factors play a substantial role in affecting the development of SNS bullying. Practically, this dissertation offers practitioners a rich and fine-grained understanding of the cause and development of SNS bullying. It also provides valuable information about the effects of the technological factors that lead to SNS bullying perpetration and bystanders' aggressive responses. Overall, this dissertation derives important insights into the prevention and intervention of SNS bullying.

abstract: Cyberbullying is a phenomenon which negatively affects individuals. Victims of the cyberbullying suffer from a range of mental issues, ranging from depression to low self-esteem. Due to the advent of the social media platforms, cyberbullying is becoming more and more prevalent. Traditional mechanisms to fight against cyberbullying include use of standards and guidelines, human moderators, use of blacklists based on profane words, and regular expressions to manually detect cyberbullying. However, these mechanisms fall short in social media and do not scale well. Users in social media use intentional evasive expressions like, obfuscation of abusive words, which necessitates the development of a sophisticated learning framework to automatically detect new cyberbullying behaviors. Cyberbullying detection in social media is a challenging task due to short, noisy and unstructured content and intentional obfuscation of the abusive words or phrases by social media users. Motivated by sociological and psychological findings on bullying behavior and its correlation with emotions, we propose to leverage the sentiment information to accurately detect cyberbullying behavior in social media by proposing an effective optimization framework. Experimental results on two real-world social media datasets show the superiority of the proposed framework. Further studies validate the effectiveness of leveraging sentiment information for cyberbullying detection. / Dissertation/Thesis / Masters Thesis Computer Science 2017

Cyberfeminist scholars have identified the Internet as a site where feminist issues are substantiated. This exploratory study investigates young women’s lived experiences of agency within online social networking, also looking at the ways in which their assertion of agency is constrained. Analysis identified four biographically consistent identity narratives within which participants experienced online agency, each with a unique operationalization of agency, constraints upon agency, and role of a heteronormative boyfriend. Identity narratives tended to invoke socially- and media-entrenched representations of how to ‘properly’ perform ‘girl’ online, including stereotypes of girls vigilantly managing online risk or portraying themselves as professional, ethically sensible, family-oriented, or popular and celebrity-oriented. However, these representations were also inherently conflictual, presenting incompatible expectations that were difficult to simultaneously negotiate. In conclusion, this study recommends that future research and policy abandon patriarchal, neoliberal underpinnings in favour of deconstructing problematic stereotyped representations of femininity within online spaces.

While bringing tremendous benefits to individuals worldwide, the proliferation of online social networks has also given rise to undesirable online harassment behavior. Although users can respond in various ways, little attention has been paid so far to the use of online coping strategies on social media, more specifically, how individuals respond to online harassment by using the available features on social media. This thesis sought to understand individuals' use of online coping strategies. This thesis aims to tackle these challenges to advance the understanding of whether, how, and why individuals use online coping strategies in response to online harassment. Essay 1 develops a typology of online coping strategies based on users' focus of response (i.e., self or initiator) and mode of response (i.e., avoidance or approach). This essay serves as a conceptual background for the two subsequent empirical studies (Essay 2 and Essay 3) that focus on two critical roles involved in online harassment (e.g., victims and bystanders). These two studies are conducted in the social media context. Essay 2 investigates whether and how individuals use online coping strategies in response to online harassment on social media. Results from a scenario-based experiment showed that victims would be more likely to adopt self-focused and approach strategies (e.g., seclusion, mediation, and reporting) when they perceived a high threat of the incident. Confidence in executing the platform functions would increase victims' use of the initiators-focused strategies in both modes (e.g., blocking and reporting) but reduce their use of self-focused avoidance strategy (e.g., seclusion). Trust in social media would lead victims to the self-focused approach strategy (e.g., mediation). Victims with the intensified fear of the incident would be more likely to use the self-focused and avoidance strategies (e.g., seclusion, mediation, and blocking). While Essay 2 focuses on the role of victims, Essay 3 concentrates on the role of bystanders and reporting strategy, which is one of the online coping strategies on social media that support bystanders' interventions. Essay 3 explains why individuals report witnessing online harassment. The results found that four contextualized factors (perceived emergency of the online harassment incident, perceived responsibility to report, perceived self-efficacy in using built-in reporting functions, and perceived outcome effectiveness of built-in reporting functions for tackling online harassment) are important factors for shaping bystander reporting interventions, while the presence of others as an inhibitor that discourages bystanders' willingness to help. This essay also found that socio- environmental and technological factors exert a significant effect on bystanders' willingness to intervene. In sum, this thesis contributes to the area of online harassment by breaking new ground for the study of users' prosocial responses to online harassment on social media. It not only furthers our understanding of online coping strategies but also provides valuable insights for practitioners to design effective coping features to combat online harassment.

Indiana University-Purdue University Indianapolis (IUPUI) / As the size of Twitter© data is increasing, so are undesirable behaviors of its users. One such undesirable behavior is cyberbullying, which could lead to catastrophic consequences. Hence, it is critical to efficiently detect cyberbullying behavior by analyzing tweets, in real-time if possible. Prevalent approaches to identifying cyberbullying are mainly stand-alone, and thus, are time-consuming. This thesis proposes a new approach called distributed-collaborative approach for cyberbullying detection. It contains a network of detection nodes, each of which is independent and capable of classifying tweets it receives. These detection nodes collaborate with each other in case they need help in classifying a given tweet. The study empirically evaluates various collaborative patterns, and it assesses the performance of each pattern in detail. Results indicate an improvement in recall and precision of the detection mechanism over the stand- alone paradigm. Further, this research analyzes scalability of the approach by increasing the number of nodes in the network. The empirical results obtained from experimentation show that the system is scalable. The study performed also incorporates the experiments that analyze behavior distributed-collaborative approach in case of failures in the system. Additionally, the proposed thesis tests this approach on a different domain, such as politics, to explore the possibility of the generalization of results.

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