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Overcoming Spammers in Twitter -- A Tale of Five Algorithms

dc.contributor.authorGayo Avello, Daniel spa
dc.contributor.authorBrenes Martínez, David José spa
dc.date.accessioned2013-01-30T12:38:09Z
dc.date.available2013-01-30T12:38:09Z
dc.date.issued2010spa
dc.identifier.urihttp://hdl.handle.net/10651/12246
dc.descriptionI Congreso Español de Recuperación de la Información, Madrid, 2010spa
dc.description.abstractMicro-blogging services such as Twitter can develop into valuable sources of up-to-date information provided the spam problem is overcome. Thus, separating the most relevant users from the spammers is a highly pertinent question for which graph centrality methods can provide an answer. In this paper we examine the vulnerability of five different algorithms to linking malpractice in Twitter and propose a first step towards ―desensitizing‖ them against such abusive behavior.en
dc.description.urihttp://www.di.uniovi.es/~dani/downloads/CERI2010-camera-ready.pdfspa
dc.language.isoeng
dc.publisherCERIspa
dc.rightsCC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/4.0/es/
dc.subjectSocial Networksen
dc.subjectTwitteen
dc.subjectSpammingen
dc.subjectGraph Centrslityen
dc.subjectPrestigewn
dc.titleOvercoming Spammers in Twitter -- A Tale of Five Algorithmseng
dc.typeinfo:eu-repo/semantics/conferenceObjectspa
dc.type.dcmitextspa


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CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
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