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Bullying is a pervasive problem in schools, but more recent attention has been given to bullying that takes place via electronic media. To study electronic bullying and aggression effectively research needs to consider the unique qualities of the electronic medium including its capacity for anonymity, disinhibition, public forum, and under-regulated content. Electronic bullying does not occur in isolation; therefore it must be studied in relation to peer processes that occur in the “real world.” Research has neither uncovered the potential “real world” precursors of electronic bullying and aggression nor has it uncovered how students perceive the harmfulness of electronic aggression. The two studies presented here fill these gaps in the literature. The first study examined the precursors of electronic bullying and victimization in a sample of grade 9 and 10 students who were followed longitudinally. Students were administered questionnaires assessing electronic bullying/victimization, perceived harm of electronic aggression, empathy, normative beliefs, and prosocial behavior. The results indicated that “real world” behaviors such as verbal bullying and prosocial behavior were precursors of electronic bullying, while victimization by social bullying and social aggression were precursors for electronic victimization. In addition, females, older students, and students with less prosocial behavior were at risk for involvement in electronic bullying. Implications for these findings include the importance of integrating interventions that foster positive behavior in the “real world” and online, particularly for students at highest risk for involvement. The second study examined students’ harm perceptions of electronic aggression and how similar behavioral and cognitive factors may also influence perceptions of electronic aggression. Cross-sectional data were collected from students in grades 7 through 9 who were administered the same questionnaires above. Electronic bullying was perceived as more harmful than physical and social aggression, particularly for girls and students with highly prosocial behavior. Thus, electronic aggression is a very serious issue for students and education is needed to change the social norms for acceptable behavior in cyberspace. Consistent with social-cognitive theory, similar demographics and behaviors predicted electronic behavior and perceptions. Future research should continue to extend the social-cognitive model to electronic conflict. / Thesis (Master, Psychology) -- Queen's University, 2009-09-22 21:15:56.732

Yes / Aggressive posts containing symbolic and offensive images, inappropriate gestures along with provocative textual comments are growing exponentially in social media with the availability of inexpensive data services. These posts have numerous negative impacts on the reader and need an immediate technical solution to filter out aggressive comments. This paper presents a model based on a Convolutional Neural Network (CNN) and Binary Particle Swarm Optimization (BPSO) to classify the social media posts containing images with associated textual comments into non-aggressive, medium-aggressive and high-aggressive classes. A dataset containing symbolic images and the corresponding textual comments was created to validate the proposed model. The framework employs a pre-trained VGG-16 to extract the image features and a three-layered CNN to extract the textual features in parallel. The hybrid feature set obtained by concatenating the image and the text features were optimized using the BPSO algorithm to extract the more relevant features. The proposed model with optimized features and Random Forest classifier achieves a weighted F1-Score of 0.74, an improvement of around 3% over unoptimized features.

Yes / Cyber-aggression is an offensive behaviour attacking people based on race, ethnicity, religion, gender, sexual orientation, and other traits. It has become a major issue plaguing the online social media. In this research, we have developed a deep learning-based model to identify different levels of aggression (direct, indirect and no aggression) in a social media post in a bilingual scenario. The model is an autoencoder built using the LSTM network and trained with non-aggressive comments only. Any aggressive comment (direct or indirect) will be regarded as an anomaly to the system and will be marked as Overtly (direct) or Covertly (indirect) aggressive comment depending on the reconstruction loss by the autoencoder. The validation results on the dataset from two popular social media sites: Facebook and Twitter with bilingual (English and Hindi) data outperformed the current state-of-the-art models with improvements of more than 11% on the test sets of the English dataset and more than 6% on the test sets of the Hindi dataset.

Работа посвящена исследованию особенностей агональной коммуникации в современных социальных сетях. Объектом исследования выступает англоязычный агональный дискурс в онлайн-среде социальных сетей, предметом – агональность как популярный тип поведения подростков, молодежи в онлайн-среде социальных сетей и лексико-синтаксические средства его объективации в английском языке. Цель исследования: описать специфику агонального поведения пользователей интернет-сообщества в сравнении двух лингвокультур. Материалом исследования послужили комментарии пользователей социальных сетей Вконтакте, Facebook, Instagram и Twitter. Дискурс в социальных сетях – тексты и высказывания, которые помогают сочетать устный и письменный варианты коммуникации. В ходе проведенного исследования на материале англоязычных комментариев в социальных сетях Facebook, Twitter и Instagram мы пришли к выводу о том, что коммуникативно-прагматические особенности агональности реализуются в виде так называемых издевательств, а именно словесных угроз, оскорблений, саркастических замечаний, адресованных другим лицам, уничижительным сравнением и даже обсценной лексикой. Выделяются такие виды киберагрессии как троллинг, флейминг, хейтинг, кибербуллинг и киберсталкинг. Интернет-среда нарушает нормы языка в процессе общения, разрешая пользователям пренебрегать существующими грамматическими (морфологическими, синтаксическими) правилами, что приводит к появлению перечисленных в данной работе отклонений. Все это свидетельствует о демократизации языка, его обновлении и развитии, коммуникативном новаторстве. В 34 % случаях агональность репрезентирована негативно-окрашенными сравнениями; агональность проявляется оценочными суждениями, негативно-окрашенной и обсценной лексикой, бранью (21 %); гипербола и антономасия передают агрессию имплицитно посредством преувеличения (гипербола) или переименования (антономасия) (18 %); стилистический прием парадокса (15 %). Такие цифры говорят о достаточно высоком уровне агрессивности поведения в цифровой среде. / The work is devoted to the study of the features of agonal communication in modern social networks. The object of the study is the English-language agonal discourse in the online environment of social networks, the subject is agonality as a popular type of behavior of adolescents and youth in the online environment of social networks and lexical and syntactic means of its objectification in English. The purpose of the study is to describe the specifics of the agonal behavior of Internet community users in comparison of two linguistic cultures. Instagram Facebook, Instagram and Twitter social media users' comments served as the research material. Discourse in social networks – texts and statements that help to combine oral and written communication options. Instagram Facebook, Twitter and Instagram social networks, we came to the conclusion that the communicative and pragmatic features of agonality are realized in the form of so-called bullying, namely verbal threats, insults, sarcastic remarks addressed to other persons, derogatory comparison and even obscene vocabulary. There are such types of cyber aggression as trolling, flaming, heiting, cyberbullying and cyberstalking. The Internet environment violates the norms of language in the process of communication, allowing users to neglect the existing grammatical (morphological, syntactic) rules, which leads to the appearance of the deviations listed in this work. All this testifies to the democratization of the language, its renewal and development, and communicative innovation. In 34% of cases, agonality is represented by negatively colored comparisons; agonality is manifested by value judgments, negatively-colored and obscene vocabulary, swearing (21%); hyperbole and antonomasia convey aggression implicitly through exaggeration (hyperbole) or renaming (antonomasia) (18%); stylistic paradox technique (15%). Such figures indicate a fairly high level of aggressive behavior in the digital environment.

Cyber aggression came about as a result of advances in information communication technology and the aggressive usage of the technology in real life. Cyber aggression can take on many forms and facets. However, the main focus of this study is cyberbullying and cyberstalking through information sharing practices that might constitute digital aggressive acts. Human aggression has been extensively investigated. Studies focusing on understanding the causes and effects that can lead to physical and digital aggression have shown the prevalence of cyber aggression in different settings. Moreover, these studies have shown strong relationship between cyber aggression and the physiological and physical trauma on both perpetrators and their victims. Nevertheless, the literature shows a lack of studies that could measure the level of acceptance and tolerance of these dangerous digital acts. This study is divided into two main stages; Stage one is a qualitative pilot study carried out to explore the concept of cyber aggression and its existence in Saudi Arabia. In-depth interviews were conducted with 14 Saudi social media users to collect understanding and meanings of cyber aggression. The researcher followed the Colaizzi’s methods to analyze the descriptive data. A proposed model was generated to describe cyber aggression in social media applications. The results showed that there is a level of acceptance to some cyber aggression acts due to a number of factors. The second stage of the study is focused on developing scales with reliable items that could determine acceptability and tolerability of cyber aggression. In this second stage, the researcher used the factors discovered during the first stage as source to create the scales’ items. The proposed methods and scales were analyzed and tested to increase reliability as indicated by the Cronbach’s Alpha value. The scales were designed to measure how acceptable and tolerable is cyber-bullying, cyber-stalking in Saudi Arabia and the sharing of some information in social media applications. The results show a strong tolerance level of those activities. This study is a valuable resource for advanced-level students, educators, and researchers who focus on cyber security, cyber psychology, and cyber aggression in social network sites.