Methodology

This study focused on recognizing the process of the emergence of gender-based online hate speech against female politicians on Czech Facebook, the multi-level categorization of these expressions, the determination of their impact on the public activity of female politicians, the identification of weak points in the prevention of these attacks and suggestions for improvement, as well as on raising awareness of adverse effects of these attacks. The approach consists of a combination of quantitative and qualitative methods, including content and semantic analysis of comments and posts from Facebook groups, questionnaires for women active in politics, interviews with politicians, media analysis, case studies and analysis of legal documents. The primary data source was comments and posts from publicly accessible Facebook groups, from January 2022 to February 2023, comprising a total of 1,816,723 comments and 154,711 posts. The data was analysed using LookerStudio and Geneea software, using artificial intelligence technologies for text analysis. A categorization of hate speech was proposed and 15% of comments containing hate speech were identified. The analysis also included tracking "waves" of hate attacks and trying to identify their "triggers", while a detailed analysis of specific cases of high incidence of hate speech was carried out. Another method was a survey among politically active women, which aimed to find out how often they encounter hate speech, how they react to it, and how this speech affects their political activity and presentation on social networks. In-depth semi-structured interviews with female politicians complemented the information obtained and allowed a deeper insight into the issue. An analysis of court decisions related to online hate speech was also included, with the aim of preparing recommendations for improving the legal framework and practice. The study also focused on the characteristics of the most active profiles in disinformation groups and the analysis of their behaviour, with the aim of understanding the dynamics of the spread of hate speech on social networks.