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Misogyny refers to the deeply ingrained bias against women, characterised by feelings of hatred, aversion, and distrust primarily due to their gender. With a large dataset of Italian-written tweets, our research aims to analyse the individuals who generate and disseminate misogynistic information. To achieve this, we first use a Graph Convolutional Network approach to categorise Twitter accounts into a binary misogyny scheme, leveraging both textual and relational data from friend/follower relationships. Then, we compare the retrieved misogynistic and non-misogynistic communities, considering both network centrality measures and linguistic features.

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Identification of Misogynistic Accounts on Twitter Through Graph Convolutional Networks

  • 会议论文

  • 出版模式：

    开放获取

  • 发表日期：

    2025年

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  • Emiliano del Gobbo,
  • Alex Cucco,
  • Lara Fontanella

摘要

Misogyny refers to the deeply ingrained bias against women, characterised by feelings of hatred, aversion, and distrust primarily due to their gender. With a large dataset of Italian-written tweets, our research aims to analyse the individuals who generate and disseminate misogynistic information. To achieve this, we first use a Graph Convolutional Network approach to categorise Twitter accounts into a binary misogyny scheme, leveraging both textual and relational data from friend/follower relationships. Then, we compare the retrieved misogynistic and non-misogynistic communities, considering both network centrality measures and linguistic features.