Overcoming Spammers in Twitter -- A Tale of Five Algorithms

dc.contributor.author	Gayo Avello, Daniel	spa
dc.contributor.author	Brenes Martínez, David José	spa
dc.date.accessioned	2013-01-30T12:38:09Z
dc.date.available	2013-01-30T12:38:09Z
dc.date.issued	2010	spa
dc.identifier.uri	http://hdl.handle.net/10651/12246
dc.description	I Congreso Español de Recuperación de la Información, Madrid, 2010	spa
dc.description.abstract	Micro-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.uri	http://www.di.uniovi.es/~dani/downloads/CERI2010-camera-ready.pdf	spa
dc.language.iso	eng
dc.publisher	CERI	spa
dc.rights	CC Reconocimiento - No comercial - Sin obras derivadas 4.0 Internacional
dc.rights.uri	http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.subject	Social Networks	en
dc.subject	Twitte	en
dc.subject	Spamming	en
dc.subject	Graph Centrslity	en
dc.subject	Prestige	wn
dc.title	Overcoming Spammers in Twitter -- A Tale of Five Algorithms	eng
dc.type	conference output	spa
dc.rights.accessRights	open access

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