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AI to prevent cyber-violence: harmful behaviour detection in social media

机译:ai防止网络暴力:社交媒体中有害行为检测

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摘要

Social media has allowed people to communicate freely. This total freedom has led to the emergence of cyber-violence with a growing number of victims. Many researches in psychology and e-health have been conducted to detect the act of cyber-violence. In computational field, most of works have focused on multiple aspects of cyber-violence, but none of them, to our knowledge, have studied the perpetrator's harmful behaviour from an emotional dimension. Our goal in this work is to discover the relationship between the emotional state of social media users and their harmful behaviour while engaged in the act of cyber-violence. Our approach is based on Ensemble Machine Learning and engineered features related to Plutchik wheel of basic emotions extracted with semantic similarity and word embedding. The results show a significant association between the individual's emotional state and the harmful intent, which may be a good indicator for cyber-violence detection.
机译:社交媒体使人们可以自由沟通。这种完全自由导致了越来越多的受害者的网络暴力。已经进行了许多心理学和电子健康的研究,以检测网络暴力行为。在计算领域,大多数作品都专注于网络暴力的多个方面,但我们的知识都没有学习犯罪者从情绪维度的有害行为。我们在这项工作中的目标是发现社交媒体用户的情感状态与他们有害行为之间的关系,同时从事网络暴力行为。我们的方法是基于与用语义相似性和单词嵌入的基本情绪的Plutchik滚轮相关的集成机器学习和工程特征。结果表明,个人的情绪状态与有害意图之间的重要关联,这可能是网络暴力检测的良好指标。

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