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Big Five Personality Traits and Ensemble Machine Learning to Detect Cyber-Violence in Social Media

  • Randa ZarnoufiEmail author
  • Mounia Abik
Conference paper
Part of the Learning and Analytics in Intelligent Systems book series (LAIS, volume 7)

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.

Keywords

E-Health Cyber-violence Social networks Harmful behavior Big Five personality Ensemble Machine Learning Features engineering 

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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.IPSS Research Team, FSRMohammed V University in RabatRabatMorocco
  2. 2.IPSS Research Team, ENSIASMohammed V University in RabatRabatMorocco

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