Discovering Structures of Communities in the #StopHateForProfit Network: A Social Network Analysis

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Autor(es): dc.contributorUniversidade Estadual Paulista (UNESP)-
Autor(es): dc.contributorUniv Leon-
Autor(es): dc.contributorUniv Complutense Madrid-
Autor(es): dc.creatorPuerta-Diaz, Mirelys-
Autor(es): dc.creatorMartinez-avila, Daniel-
Autor(es): dc.creatorPeradones, Maria Antonia Ovalle-
Data de aceite: dc.date.accessioned2025-08-21T19:21:38Z-
Data de disponibilização: dc.date.available2025-08-21T19:21:38Z-
Data de envio: dc.date.issued2025-04-29-
Data de envio: dc.date.issued2024-07-01-
Fonte completa do material: dc.identifierhttps://hdl.handle.net/11449/301162-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/11449/301162-
Descrição: dc.descriptionThe 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-
Descrição: dc.descriptionUniv Estadual Paulista Julio De Mesquita Filho UNE, Fac Filosofia & Ciencias, Dept Ciencia Informacao, Sao Paulo, Brazil-
Descrição: dc.descriptionUniv Leon, Fac Filosofia & Letras, Dept Bibliotecon Documentac, Leon, Spain-
Descrição: dc.descriptionUniv Complutense Madrid, Fac Filosofia & Letras, Dept Bibliotecon Documentac, Madrid, Spain-
Descrição: dc.descriptionUniv Estadual Paulista Julio De Mesquita Filho UNE, Fac Filosofia & Ciencias, Dept Ciencia Informacao, Sao Paulo, Brazil-
Formato: dc.format163-183-
Idioma: dc.languagees-
Publicador: dc.publisherUniv Nacional Autonoma Mexico-
Relação: dc.relationInvestigacion Bibliotecologica-
???dc.source???: dc.sourceWeb of Science-
Palavras-chave: dc.subject#StopHateForProfit-
Palavras-chave: dc.subjectHate Speech-
Palavras-chave: dc.subjectSocial Network Analysis-
Palavras-chave: dc.subjectCommunities Detection-
Título: dc.titleDiscovering Structures of Communities in the #StopHateForProfit Network: A Social Network Analysis-
Tipo de arquivo: dc.typelivro digital-
Aparece nas coleções:Repositório Institucional - Unesp

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