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Automatic cyberbullying detection: A systematic review

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dc.contributor.authorRosa, Hugo
dc.contributor.authorSalgado Pereira, Nádia
dc.contributor.authorRibeiro, Ricardo
dc.contributor.authorFerreira, Paula
dc.contributor.authorCarvalho, Joao P.
dc.contributor.authorOliveira, Sofia
dc.contributor.authorCoheur, Luisa
dc.contributor.authorPaulino, Paula
dc.contributor.authorVeiga Simão, Ana
dc.contributor.authorTrancoso, Isabel
dc.date.accessioned2024-02-11T20:14:30Z
dc.date.available2024-02-11T20:14:30Z
dc.date.issued2019-04
dc.date.updated2024-01-31T22:09:05Z
dc.description.abstractAutomatic 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.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationRosa, 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.2018.12.021pt_PT
dc.identifier.doi10.1016/j.chb.2018.12.021pt_PT
dc.identifier.issn0747-5632
dc.identifier.slugcv-prod-247111
dc.identifier.urihttp://hdl.handle.net/10451/62581
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relation.publisherversionhttps://www.sciencedirect.com/science/article/abs/pii/S0747563218306071pt_PT
dc.subjectCyberbullyingpt_PT
dc.subjectAutomatic cyberbullying detectionpt_PT
dc.subjectNatural language processingpt_PT
dc.subjectMachine learningpt_PT
dc.subjectAbusive languagept_PT
dc.subjectSocial networkspt_PT
dc.titleAutomatic cyberbullying detection: A systematic reviewpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.citation.endPage345pt_PT
oaire.citation.startPage333pt_PT
oaire.citation.titleComputers in Human Behaviorpt_PT
oaire.citation.volume93pt_PT
person.familyNameSalgado Pereira
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person.familyNameda Costa Ferreira
person.familyNameBaptista de Carvalho
person.familyNameViegas de Oliveira Francisco
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person.familyNamePaulino
person.familyNameVeiga Simão
person.familyNameTrancoso
person.givenNameNádia
person.givenNameRicardo
person.givenNamePaula Alexandra Nunes
person.givenNameJoão Paulo
person.givenNameAna Sofia
person.givenNameLuisa
person.givenNamePaula
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person.givenNameIsabel
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rcaap.cv.cienciaid7115-EC2B-AEAC | Paula Alexandra Nunes da Costa Ferreira
rcaap.rightsclosedAccesspt_PT
rcaap.typearticlept_PT
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