Identifying themes in online harassment using text analytics
Researcher: Miss Safiyyah Ismail, The University of the Witwatersrand
Supervisor: Professor Rod Alence, University of the Witwatersrand, Johannesburg
Nothing quite affects human behaviour as much as the internet. With a cloak of invisibility and anonymity in cyberspace, a new phenomenon known as cyberharassment has been created. It is suggested that these behaviours are magnified online due to the Online Disinhibiton Effect and Deindividuation ; and occur under 5 major themes: political, racial/religious, sexual, appearance-related, and intelligence-related. Thus, the current study aimed to provide a mixed-method analysis of textual data to explore the nature of cyber-harassment on Twitter – a popular social networking platform well-known for aggressive and hostile online behaviours. Latent Dirichlet Allocation (LDA) Topic Modelling was used to explore the nature of online harassment by identifying key themes online. Results found that political and racial/religious themes are most prevalent online. The current research study has contributed to existing literature by exploring the nature of existing themes which have been identified in online harassment. While the results did not adequately address the proposed question, it forms part of the foundation to understanding the nature of online behaviours.