DARK SIDE OF THE DIGITAL WORLD: Computational Analysis of Negative Human Behaviors on Social Media
| Autor: | Jabeen, Fakhra |
|---|---|
| Přispěvatelé: | Treur, Jan, Gerritsen, Charlotte, Faculty of Science, Social AI, Artificial intelligence, Business Informatica |
| Jazyk: | angličtina |
| Rok vydání: | 2022 |
| Předmět: |
Cyber Aggression
Cyber Agressie Narcissism on Social Media Narcisme op sociale media Emotion regulation Supporting victims of the negative behaviors Predicting Narcissism on Social Media Narcisme voorspellen op sociale media Emotie regulatie Computationele modellering en analyse Computational Modeling and Analysis Slachtoffers van negatief gedrag ondersteunen |
| Popis: | Social media have given a dimension that is beyond any geographical limits, which is growing tremendously. It has been useful in providing real-time communication opportunities; however, its massive usage has its own pitfalls. This thesis aims to address two possible human behaviors in the context of social media usage, i.e., aggression and narcissism. The deeper impact of each of these behaviors is studied by designing mathematical models, simulating them based on multidisciplinary literature, and verifying them by applying analysis and machine learning techniques. Each behavior is modeled through computational network-based modeling, which uses the multidisciplinary literature available. These models are causal by nature and indicate the factors that can lead to such behaviors. After simulating these models, their behavior has been validated empirically using qualitative empirical information from the literature and real-world data, for example, by analyzing conversational tweets through Language Processing or analyzing quantitative questionnaire data. While discussing the aggressors and narcissists, the thesis also presents computational models for the sufferer of these behaviors, along with the possible regulation to feel better and supported. During the analysis of data, the dynamics of the designed models were studied in particular. All models were declarative by nature and were studied mostly in combination with the analysis of the longitudinal qualitative data collected from social media over time, or by the analysis of quantitative data from surveys. Thus, this thesis provides a significant contribution to the state of the art, by providing a sound basis for modeling and predicting specific negative behaviors on social media by performing data analytics, which can be extended to study these behaviors in-depth and to provide related support. |
| Databáze: | OpenAIRE |
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