Mane, Swapnil, juhendajaSharma, Rajesh, juhendajaKundu, Suman, juhendajaKvirikashvili, KetevaniTartu Ülikool. Loodus- ja täppisteaduste valdkondTartu Ülikool. Arvutiteaduse instituut2023-06-122023-06-122023https://hdl.handle.net/10062/90495Recently, the expression of aggression in social networks has increased a lot, which also causes a lot of adverse effects, such as mental health problems or some other controversies. Hence we perform the first ever user aggressive behavior analysis on Twitter social media official microblogging site, which has no restriction on aggressive behavior. Using the proposed pipeline, we study the user’s aggressive behavior. The pipeline is based on three stages such as data collection, aggression detection, and user profiling. In this study, we detailed analyzed the aggressive behavior of users are depends on their aggressive feeds and events. Further, our analysis revealed that user engagement is higher in aggressive posts.engopenAccessAttribution-NonCommercial-NoDerivatives 4.0 InternationalOnline Social MediaAggression DetectionAggressive Behaviour AnalysismagistritöödinformaatikainfotehnoloogiainformaticsinfotechnologyThesis