Learning for Detecting Norm Violation in Online Communities

[EN]In this paper, we focus on normative systems for online communities. The paper addresses the issue that arises when different community members interpret these norms in different ways, possibly leading to unexpected behavior in interactions, usually with norm violations that affect the individua...

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Detalles Bibliográficos
Autores: Freitas dos Santos, Thiago, Osman, Nardine, Schorlemmer, Marco
Tipo de recurso: artículo
Estado:Versión enviada para evaluación y publicación
Fecha de publicación:2021
País:España
Institución:Consejo Superior de Investigaciones Científicas (CSIC)
Repositorio:DIGITAL.CSIC. Repositorio Institucional del CSIC
OAI Identifier:oai:digital.csic.es:10261/241162
Acceso en línea:http://hdl.handle.net/10261/241162
Access Level:acceso abierto
Palabra clave:Norms
Norm Violation Detection
Machine learning
Wikipedia Norms
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repository_id_str
spelling Learning for Detecting Norm Violation in Online CommunitiesFreitas dos Santos, ThiagoOsman, NardineSchorlemmer, MarcoNormsNorm Violation DetectionMachine learningWikipedia Norms[EN]In this paper, we focus on normative systems for online communities. The paper addresses the issue that arises when different community members interpret these norms in different ways, possibly leading to unexpected behavior in interactions, usually with norm violations that affect the individual and community experiences. To address this issue, we propose a framework capable of detecting norm violations and providing the violator with information about the features of their action that makes this action violate a norm. We build our framework using Machine Learning, with Logistic Model Trees as the classification algorithm. Since norm violations can be highly contextual, we train our model using data from the Wikipedia online community, namely data on Wikipedia edits. Our work is then evaluated with the Wikipedia use case where we focus on the norm that prohibits vandalism in Wikipedia edits.Peer reviewedarXivOsman, Nardine [0000-0002-2766-3475]Schorlemmer, Marco [0000-0002-9591-3325]Freitas Dos Santos, Thiago [0000-0003-3800-7243]Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]202120212021info:eu-repo/semantics/articlehttp://purl.org/coar/resource_type/c_6501Preprintinfo:eu-repo/semantics/submittedVersionhttp://hdl.handle.net/10261/241162reponame:DIGITAL.CSIC. Repositorio Institucional del CSICinstname:Consejo Superior de Investigaciones Científicas (CSIC)InglésSíinfo:eu-repo/semantics/openAccessoai:digital.csic.es:10261/2411622026-05-22T06:33:51Z
dc.title.none.fl_str_mv Learning for Detecting Norm Violation in Online Communities
title Learning for Detecting Norm Violation in Online Communities
spellingShingle Learning for Detecting Norm Violation in Online Communities
Freitas dos Santos, Thiago
Norms
Norm Violation Detection
Machine learning
Wikipedia Norms
title_short Learning for Detecting Norm Violation in Online Communities
title_full Learning for Detecting Norm Violation in Online Communities
title_fullStr Learning for Detecting Norm Violation in Online Communities
title_full_unstemmed Learning for Detecting Norm Violation in Online Communities
title_sort Learning for Detecting Norm Violation in Online Communities
dc.creator.none.fl_str_mv Freitas dos Santos, Thiago
Osman, Nardine
Schorlemmer, Marco
author Freitas dos Santos, Thiago
author_facet Freitas dos Santos, Thiago
Osman, Nardine
Schorlemmer, Marco
author_role author
author2 Osman, Nardine
Schorlemmer, Marco
author2_role author
author
dc.contributor.none.fl_str_mv Osman, Nardine [0000-0002-2766-3475]
Schorlemmer, Marco [0000-0002-9591-3325]
Freitas Dos Santos, Thiago [0000-0003-3800-7243]
Consejo Superior de Investigaciones Científicas [https://ror.org/02gfc7t72]
dc.subject.none.fl_str_mv Norms
Norm Violation Detection
Machine learning
Wikipedia Norms
topic Norms
Norm Violation Detection
Machine learning
Wikipedia Norms
description [EN]In this paper, we focus on normative systems for online communities. The paper addresses the issue that arises when different community members interpret these norms in different ways, possibly leading to unexpected behavior in interactions, usually with norm violations that affect the individual and community experiences. To address this issue, we propose a framework capable of detecting norm violations and providing the violator with information about the features of their action that makes this action violate a norm. We build our framework using Machine Learning, with Logistic Model Trees as the classification algorithm. Since norm violations can be highly contextual, we train our model using data from the Wikipedia online community, namely data on Wikipedia edits. Our work is then evaluated with the Wikipedia use case where we focus on the norm that prohibits vandalism in Wikipedia edits.
publishDate 2021
dc.date.none.fl_str_mv 2021
2021
2021
dc.type.none.fl_str_mv info:eu-repo/semantics/article
http://purl.org/coar/resource_type/c_6501
Preprint
info:eu-repo/semantics/submittedVersion
format article
status_str submittedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/10261/241162
url http://hdl.handle.net/10261/241162
dc.language.none.fl_str_mv Inglés
language_invalid_str_mv Inglés
dc.relation.none.fl_str_mv Sí
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.publisher.none.fl_str_mv arXiv
publisher.none.fl_str_mv arXiv
dc.source.none.fl_str_mv reponame:DIGITAL.CSIC. Repositorio Institucional del CSIC
instname:Consejo Superior de Investigaciones Científicas (CSIC)
instname_str Consejo Superior de Investigaciones Científicas (CSIC)
reponame_str DIGITAL.CSIC. Repositorio Institucional del CSIC
collection DIGITAL.CSIC. Repositorio Institucional del CSIC
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repository.mail.fl_str_mv
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score 15.811543

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