Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns

Detalhes bibliográficos
Autor(a) principal: Fonseca, A.
Data de Publicação: 2024
Outros Autores: Pontes, C., Moro, S., Batista, F., Ribeiro, R., Guerra, R., Carvalho, P., Marques, C., Silva, C.
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
Texto Completo: http://hdl.handle.net/10071/31800
Resumo: This paper investigates the pervasive issue of hate speech within Twitter/X Portuguese network conversations, offering a multifaceted analysis of its characteristics. This study utilizes a mixed-method approach, combining several methodologies of network analysis (triad census and participation shifts) over the network of interaction between users. Qualitative manual content annotation was applied to the dataset to dissect different patterns of hate speech on the platform. Key findings reveal that the number of users followed by an individual and potentially reads is a relevant predictor for a user's propensity to post aggressive content. We concluded also that during a conversation thread, hate speech happens significantly more within the first 2 h of interaction. Transitivity of interactions and individual expression are considerably lower as more hate speech is prevalent in conversations. Our research confirms that hate speech is usually expressed by external individuals who intrude into conversations. Conversely, the expression of hate speech of indirect type by third parties interfering in conversations is uncommon. We also found that counter-speech discourse is strongly correlated with a type of discourse that typically avoids conflict and is not privately held.
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spelling Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patternsThis paper investigates the pervasive issue of hate speech within Twitter/X Portuguese network conversations, offering a multifaceted analysis of its characteristics. This study utilizes a mixed-method approach, combining several methodologies of network analysis (triad census and participation shifts) over the network of interaction between users. Qualitative manual content annotation was applied to the dataset to dissect different patterns of hate speech on the platform. Key findings reveal that the number of users followed by an individual and potentially reads is a relevant predictor for a user's propensity to post aggressive content. We concluded also that during a conversation thread, hate speech happens significantly more within the first 2 h of interaction. Transitivity of interactions and individual expression are considerably lower as more hate speech is prevalent in conversations. Our research confirms that hate speech is usually expressed by external individuals who intrude into conversations. Conversely, the expression of hate speech of indirect type by third parties interfering in conversations is uncommon. We also found that counter-speech discourse is strongly correlated with a type of discourse that typically avoids conflict and is not privately held.Elsevier2024-06-03T08:50:09Z2024-01-01T00:00:00Z20242024-06-03T09:47:55Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10071/31800eng2405-844010.1016/j.heliyon.2024.e32246Fonseca, A.Pontes, C.Moro, S.Batista, F.Ribeiro, R.Guerra, R.Carvalho, P.Marques, C.Silva, C.info:eu-repo/semantics/openAccessreponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãoinstacron:RCAAP2024-07-07T03:00:39Zoai:repositorio.iscte-iul.pt:10071/31800Portal AgregadorONGhttps://www.rcaap.pt/oai/openairemluisa.alvim@gmail.comopendoar:71602024-07-07T03:00:39Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informaçãofalse
dc.title.none.fl_str_mv Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
title Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
spellingShingle Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
Fonseca, A.
title_short Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
title_full Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
title_fullStr Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
title_full_unstemmed Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
title_sort Analyzing hate speech dynamics on Twitter/X: Insights from conversational data and the impact of user interaction patterns
author Fonseca, A.
author_facet Fonseca, A.
Pontes, C.
Moro, S.
Batista, F.
Ribeiro, R.
Guerra, R.
Carvalho, P.
Marques, C.
Silva, C.
author_role author
author2 Pontes, C.
Moro, S.
Batista, F.
Ribeiro, R.
Guerra, R.
Carvalho, P.
Marques, C.
Silva, C.
author2_role author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Fonseca, A.
Pontes, C.
Moro, S.
Batista, F.
Ribeiro, R.
Guerra, R.
Carvalho, P.
Marques, C.
Silva, C.
description This paper investigates the pervasive issue of hate speech within Twitter/X Portuguese network conversations, offering a multifaceted analysis of its characteristics. This study utilizes a mixed-method approach, combining several methodologies of network analysis (triad census and participation shifts) over the network of interaction between users. Qualitative manual content annotation was applied to the dataset to dissect different patterns of hate speech on the platform. Key findings reveal that the number of users followed by an individual and potentially reads is a relevant predictor for a user's propensity to post aggressive content. We concluded also that during a conversation thread, hate speech happens significantly more within the first 2 h of interaction. Transitivity of interactions and individual expression are considerably lower as more hate speech is prevalent in conversations. Our research confirms that hate speech is usually expressed by external individuals who intrude into conversations. Conversely, the expression of hate speech of indirect type by third parties interfering in conversations is uncommon. We also found that counter-speech discourse is strongly correlated with a type of discourse that typically avoids conflict and is not privately held.
publishDate 2024
dc.date.none.fl_str_mv 2024-06-03T08:50:09Z
2024-01-01T00:00:00Z
2024
2024-06-03T09:47:55Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/10071/31800
url http://hdl.handle.net/10071/31800
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 2405-8440
10.1016/j.heliyon.2024.e32246
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dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Elsevier
publisher.none.fl_str_mv Elsevier
dc.source.none.fl_str_mv reponame:Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
instname:Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron:RCAAP
instname_str Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
instacron_str RCAAP
institution RCAAP
reponame_str Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
collection Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos)
repository.name.fl_str_mv Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação
repository.mail.fl_str_mv mluisa.alvim@gmail.com
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