Abstract
Cyber-violence is a largely addressed problem in e-health researches, its focus is the detection of harmful behavior from online user-generated content in order to prevent and protect victims. In this work, we show how big five personality traits are correlated to the violent behavior of the cyber-violence perpetrator. We use a set of ensemble learning algorithms with engineered features related to the vocabulary used in each Big Five personality trait namely, Agreeableness, Conscientiousness, Extraversion, Neuroticism and Openness. The findings show a significant association between the individuals’ personality state and the harmful intention. This result can be a good indicator of online users’ susceptibility to cyber-violence and therefore can help in dealing with it.
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Scikit-Learn is an open source python machine learning library.
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Zarnoufi, R., Abik, M. (2020). Big Five Personality Traits and Ensemble Machine Learning to Detect Cyber-Violence in Social Media. In: Serrhini, M., Silva, C., Aljahdali, S. (eds) Innovation in Information Systems and Technologies to Support Learning Research. EMENA-ISTL 2019. Learning and Analytics in Intelligent Systems, vol 7. Springer, Cham. https://doi.org/10.1007/978-3-030-36778-7_21
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DOI: https://doi.org/10.1007/978-3-030-36778-7_21
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