Discovering Structures of Communities in the #StopHateForProfit Network: A Social Network Analysis
The boycott campaign against Facebook #StopHate - ForProfit, launched in June 2020, emerged as a key phe - nomenon in the fight against hate speech on social media. This study addresses the detection and characterization of communities in the #StopHateForProfit campaign, employing theoretical and me...
| Autores: | , , |
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| Tipo de recurso: | artículo |
| Estado: | Versión publicada |
| Fecha de publicación: | 2024 |
| País: | Brasil |
| Institución: | Universidade Estadual Paulista (UNESP) |
| Repositorio: | Repositório Institucional da UNESP |
| Idioma: | español |
| OAI Identifier: | oai:repositorio.unesp.br:11449/301162 |
| Acceso en línea: | https://hdl.handle.net/11449/301162 |
| Access Level: | acceso abierto |
| Palabra clave: | #StopHateForProfit Hate Speech Social Network Analysis Communities Detection |
| Sumario: | The boycott campaign against Facebook #StopHate - ForProfit, launched in June 2020, emerged as a key phe - nomenon in the fight against hate speech on social media. This study addresses the detection and characterization of communities in the #StopHateForProfit campaign, employing theoretical and methodological approaches from Social Network Analysis ( SNA ) and Natural Lan - guage Processing ( NLP ) to examine the social structure of the campaign on Twitter (now X). We used the software Gephi for community detection, employing centrality, modularity, connected components, and clustering coef - ficient measures. The analysis disclosed a complex and cohesive network composed of 5,556 communities with a high modularity that indicated dense internal interac - tions. We identified the strongest and weakest connected actors in the communities, which hinted at the closest and most direct relationships. The classification of actors ac - cording to their position provided insight into node influ - ence and cohesion in the network. This interdisciplinary line of action contributes to understanding the diversity of approaches within the #StopHateForProfit campaign, highlighting its relevance regarding mass participation and impact. The analysis of communities revealed an ef - fective collaboration among actors, demonstrating the comprehensiveness of the coordinated strategy to counter hate speech |
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