Toxicity in Evolving Twitter Topics

Bibliographic Details
Main Author: Geller, Marcel
Publication Date: 2023
Other Authors: Vasconcelos, Vítor V., Pinheiro, Flávio l.
Language: eng
Source: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
Download full: http://hdl.handle.net/10362/154813
Summary: Geller, M., Vasconcelos, V. V., & Pinheiro, F. L. (2023). Toxicity in Evolving Twitter Topics. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science: Computational Science – ICCS 2023 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV (pp. 40-54). Article Chapter 4 (Lecture Notes in Computer Science; Vol. 14076). Springer. https://doi.org/10.1007/978-3-031-36027-5_4
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spelling Toxicity in Evolving Twitter TopicsSocial Media PlatformsTwitterTopic ModellingTopic EvolutionDiscourse ToxicityTheoretical Computer ScienceComputer Science(all)SDG 11 - Sustainable Cities and CommunitiesSDG 16 - Peace, Justice and Strong InstitutionsGeller, M., Vasconcelos, V. V., & Pinheiro, F. L. (2023). Toxicity in Evolving Twitter Topics. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science: Computational Science – ICCS 2023 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV (pp. 40-54). Article Chapter 4 (Lecture Notes in Computer Science; Vol. 14076). Springer. https://doi.org/10.1007/978-3-031-36027-5_4Tracking the evolution of discussions on online social spaces is essential to assess populations’ main tendencies and concerns worldwide. This paper investigates the relationship between topic evolution and speech toxicity on Twitter. We construct a Dynamic Topic Evolution Model (DyTEM) based on a corpus of collected tweets. To build DyTEM, we leverage a combination of traditional static Topic Modelling approaches and sentence embeddings using sBERT, a state-of-the-art sentence transformer. The DyTEM is represented as a directed graph. Then, we propose a hashtag-based method to validate the consistency of the DyTEM and provide guidance for the hyperparameter selection. Our study identifies five evolutionary steps or Topic Transition Types: Topic Stagnation, Topic Merge, Topic Split, Topic Disappearance, and Topic Emergence. We utilize a speech toxicity classification model to analyze toxicity dynamics in topic evolution, comparing the Topic Transition Types in terms of their toxicity. Our results reveal a positive correlation between the popularity of a topic and its toxicity, with no statistically significant difference in the presence of inflammatory speech among the different transition types. These findings, along with the methods introduced in this paper, have broader implications for understanding and monitoring the impact of topic evolution on the online discourse, which can potentially inform interventions and policy-making in addressing toxic behavior in digital communities.SpringerNOVA Information Management School (NOVA IMS)Information Management Research Center (MagIC) - NOVA Information Management SchoolRUNGeller, MarcelVasconcelos, Vítor V.Pinheiro, Flávio l.2024-10-15T00:30:44Z2023-06-262023-06-26T00:00:00Zconference objectinfo:eu-repo/semantics/publishedVersion15application/pdfhttp://hdl.handle.net/10362/154813eng978-3-031-36026-80302-9743PURE: 65185057https://doi.org/10.1007/978-3-031-36027-5_4info:eu-repo/semantics/openAccessreponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiainstacron:RCAAP2024-10-21T01:36:45Zoai:run.unl.pt:10362/154813Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireinfo@rcaap.ptopendoar:https://opendoar.ac.uk/repository/71602025-05-28T17:42:53.278283Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologiafalse
dc.title.none.fl_str_mv Toxicity in Evolving Twitter Topics
title Toxicity in Evolving Twitter Topics
spellingShingle Toxicity in Evolving Twitter Topics
Geller, Marcel
Social Media Platforms
Twitter
Topic Modelling
Topic Evolution
Discourse Toxicity
Theoretical Computer Science
Computer Science(all)
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
title_short Toxicity in Evolving Twitter Topics
title_full Toxicity in Evolving Twitter Topics
title_fullStr Toxicity in Evolving Twitter Topics
title_full_unstemmed Toxicity in Evolving Twitter Topics
title_sort Toxicity in Evolving Twitter Topics
author Geller, Marcel
author_facet Geller, Marcel
Vasconcelos, Vítor V.
Pinheiro, Flávio l.
author_role author
author2 Vasconcelos, Vítor V.
Pinheiro, Flávio l.
author2_role author
author
dc.contributor.none.fl_str_mv NOVA Information Management School (NOVA IMS)
Information Management Research Center (MagIC) - NOVA Information Management School
RUN
dc.contributor.author.fl_str_mv Geller, Marcel
Vasconcelos, Vítor V.
Pinheiro, Flávio l.
dc.subject.por.fl_str_mv Social Media Platforms
Twitter
Topic Modelling
Topic Evolution
Discourse Toxicity
Theoretical Computer Science
Computer Science(all)
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
topic Social Media Platforms
Twitter
Topic Modelling
Topic Evolution
Discourse Toxicity
Theoretical Computer Science
Computer Science(all)
SDG 11 - Sustainable Cities and Communities
SDG 16 - Peace, Justice and Strong Institutions
description Geller, M., Vasconcelos, V. V., & Pinheiro, F. L. (2023). Toxicity in Evolving Twitter Topics. In J. Mikyška, C. de Mulatier, M. Paszynski, V. V. Krzhizhanovskaya, J. J. Dongarra, & P. M. A. Sloot (Eds.), Computational Science: Computational Science – ICCS 2023 23rd International Conference, Prague, Czech Republic, July 3–5, 2023, Proceedings, Part IV (pp. 40-54). Article Chapter 4 (Lecture Notes in Computer Science; Vol. 14076). Springer. https://doi.org/10.1007/978-3-031-36027-5_4
publishDate 2023
dc.date.none.fl_str_mv 2023-06-26
2023-06-26T00:00:00Z
2024-10-15T00:30:44Z
dc.type.driver.fl_str_mv conference object
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dc.identifier.uri.fl_str_mv http://hdl.handle.net/10362/154813
url http://hdl.handle.net/10362/154813
dc.language.iso.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv 978-3-031-36026-8
0302-9743
PURE: 65185057
https://doi.org/10.1007/978-3-031-36027-5_4
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eu_rights_str_mv openAccess
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dc.publisher.none.fl_str_mv Springer
publisher.none.fl_str_mv Springer
dc.source.none.fl_str_mv reponame:Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
instname:FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
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reponame_str Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
collection Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
repository.name.fl_str_mv Repositórios Científicos de Acesso Aberto de Portugal (RCAAP) - FCCN, serviços digitais da FCT – Fundação para a Ciência e a Tecnologia
repository.mail.fl_str_mv info@rcaap.pt
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