Automatic cyberbullying detection: A systematic review
Autor(a) principal: | |
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Data de Publicação: | 2019 |
Outros Autores: | , , , , , , , , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
Texto Completo: | http://hdl.handle.net/10451/62581 |
Resumo: | Automatic cyberbullying detection is a task of growing interest, particularly in the Natural Language Processing and Machine Learning communities. Not only is it challenging, but it is also a relevant need given how social networks have become a vital part of individuals' lives and how dire the consequences of cyberbullying can be, especially among adolescents. In this work, we conduct an in-depth analysis of 22 studies on automatic cyberbullying detection, complemented by an experiment to validate current practices through the analysis of two datasets. Results indicated that cyberbullying is often misrepresented in the literature, leading to inaccurate systems that would have little real-world application. Criteria concerning cyberbullying definitions and other methodological concerns seem to be often dismissed. Additionally, there is no uniformity regarding the methodology to evaluate said systems and the natural imbalance of datasets remains an issue. This paper aims to direct future research on the subject towards a viewpoint that is more coherent with the definition and representation of the phenomenon, so that future systems can have a practical and impactful application. Recommendations on future works are also made. |
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Automatic cyberbullying detection: A systematic reviewCyberbullyingAutomatic cyberbullying detectionNatural language processingMachine learningAbusive languageSocial networksAutomatic cyberbullying detection is a task of growing interest, particularly in the Natural Language Processing and Machine Learning communities. Not only is it challenging, but it is also a relevant need given how social networks have become a vital part of individuals' lives and how dire the consequences of cyberbullying can be, especially among adolescents. In this work, we conduct an in-depth analysis of 22 studies on automatic cyberbullying detection, complemented by an experiment to validate current practices through the analysis of two datasets. Results indicated that cyberbullying is often misrepresented in the literature, leading to inaccurate systems that would have little real-world application. Criteria concerning cyberbullying definitions and other methodological concerns seem to be often dismissed. Additionally, there is no uniformity regarding the methodology to evaluate said systems and the natural imbalance of datasets remains an issue. This paper aims to direct future research on the subject towards a viewpoint that is more coherent with the definition and representation of the phenomenon, so that future systems can have a practical and impactful application. Recommendations on future works are also made.ElsevierRepositório da Universidade de LisboaRosa, HugoSalgado Pereira, NádiaRibeiro, RicardoFerreira, PaulaCarvalho, Joao P.Oliveira, SofiaCoheur, LuisaPaulino, PaulaVeiga Simão, AnaTrancoso, Isabel2024-02-11T20:14:30Z2019-042024-01-31T22:09:05Z2019-04-01T00:00:00Zinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleapplication/pdfhttp://hdl.handle.net/10451/62581engRosa, H., Pereira, N., Ribeiro, R., Ferreira, P. C., Carvalho, J. P., Oliveira, S., Coheur, L., Paulino, P., Veiga Simão, A. M., & Trancoso, I. (2019). Automatic cyberbullying detection: A systematic review. Computers in Human Behavior, 93, 333-345. https://doi.org/10.1016/j.chb.2018.12.0210747-5632cv-prod-24711110.1016/j.chb.2018.12.021metadata only accessinfo: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:RCAAP2024-02-19T01:18:43Zoai:repositorio.ul.pt:10451/62581Portal AgregadorONGhttps://www.rcaap.pt/oai/openaireopendoar:71602024-03-20T02:38:52.902326Repositório 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 |
Automatic cyberbullying detection: A systematic review |
title |
Automatic cyberbullying detection: A systematic review |
spellingShingle |
Automatic cyberbullying detection: A systematic review Rosa, Hugo Cyberbullying Automatic cyberbullying detection Natural language processing Machine learning Abusive language Social networks |
title_short |
Automatic cyberbullying detection: A systematic review |
title_full |
Automatic cyberbullying detection: A systematic review |
title_fullStr |
Automatic cyberbullying detection: A systematic review |
title_full_unstemmed |
Automatic cyberbullying detection: A systematic review |
title_sort |
Automatic cyberbullying detection: A systematic review |
author |
Rosa, Hugo |
author_facet |
Rosa, Hugo Salgado Pereira, Nádia Ribeiro, Ricardo Ferreira, Paula Carvalho, Joao P. Oliveira, Sofia Coheur, Luisa Paulino, Paula Veiga Simão, Ana Trancoso, Isabel |
author_role |
author |
author2 |
Salgado Pereira, Nádia Ribeiro, Ricardo Ferreira, Paula Carvalho, Joao P. Oliveira, Sofia Coheur, Luisa Paulino, Paula Veiga Simão, Ana Trancoso, Isabel |
author2_role |
author author author author author author author author author |
dc.contributor.none.fl_str_mv |
Repositório da Universidade de Lisboa |
dc.contributor.author.fl_str_mv |
Rosa, Hugo Salgado Pereira, Nádia Ribeiro, Ricardo Ferreira, Paula Carvalho, Joao P. Oliveira, Sofia Coheur, Luisa Paulino, Paula Veiga Simão, Ana Trancoso, Isabel |
dc.subject.por.fl_str_mv |
Cyberbullying Automatic cyberbullying detection Natural language processing Machine learning Abusive language Social networks |
topic |
Cyberbullying Automatic cyberbullying detection Natural language processing Machine learning Abusive language Social networks |
description |
Automatic cyberbullying detection is a task of growing interest, particularly in the Natural Language Processing and Machine Learning communities. Not only is it challenging, but it is also a relevant need given how social networks have become a vital part of individuals' lives and how dire the consequences of cyberbullying can be, especially among adolescents. In this work, we conduct an in-depth analysis of 22 studies on automatic cyberbullying detection, complemented by an experiment to validate current practices through the analysis of two datasets. Results indicated that cyberbullying is often misrepresented in the literature, leading to inaccurate systems that would have little real-world application. Criteria concerning cyberbullying definitions and other methodological concerns seem to be often dismissed. Additionally, there is no uniformity regarding the methodology to evaluate said systems and the natural imbalance of datasets remains an issue. This paper aims to direct future research on the subject towards a viewpoint that is more coherent with the definition and representation of the phenomenon, so that future systems can have a practical and impactful application. Recommendations on future works are also made. |
publishDate |
2019 |
dc.date.none.fl_str_mv |
2019-04 2019-04-01T00:00:00Z 2024-02-11T20:14:30Z 2024-01-31T22:09:05Z |
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/10451/62581 |
url |
http://hdl.handle.net/10451/62581 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
Rosa, H., Pereira, N., Ribeiro, R., Ferreira, P. C., Carvalho, J. P., Oliveira, S., Coheur, L., Paulino, P., Veiga Simão, A. M., & Trancoso, I. (2019). Automatic cyberbullying detection: A systematic review. Computers in Human Behavior, 93, 333-345. https://doi.org/10.1016/j.chb.2018.12.021 0747-5632 cv-prod-247111 10.1016/j.chb.2018.12.021 |
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metadata only access info:eu-repo/semantics/openAccess |
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metadata only access |
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openAccess |
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application/pdf |
dc.publisher.none.fl_str_mv |
Elsevier |
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Elsevier |
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Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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RCAAP |
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RCAAP |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) |
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Repositório Científico de Acesso Aberto de Portugal (Repositórios Cientìficos) - Agência para a Sociedade do Conhecimento (UMIC) - FCT - Sociedade da Informação |
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