Pollution, bad-mouthing, and local marketing : the underground of location-based social networks.

Registro completo de metadados
MetadadosDescriçãoIdioma
Autor(es): dc.creatorCosta, Helen-
Autor(es): dc.creatorMerschmann, Luiz Henrique de Campos-
Autor(es): dc.creatorBarth, Fabrício-
Autor(es): dc.creatorBenevenuto, Fabrício Rodrigues-
Data de aceite: dc.date.accessioned2019-11-06T13:32:03Z-
Data de disponibilização: dc.date.available2019-11-06T13:32:03Z-
Data de envio: dc.date.issued2015-01-28-
Data de envio: dc.date.issued2015-01-28-
Data de envio: dc.date.issued2014-
Fonte completa do material: dc.identifierhttp://www.repositorio.ufop.br/handle/123456789/4416-
Fonte: dc.identifier.urihttp://educapes.capes.gov.br/handle/capes/557434-
Descrição: dc.descriptionLocation Based Social Networks (LBSNs) are new Web 2.0 systems that are attracting new users in exponential rates. LBSNs like Foursquare and Yelp allow users to share their geographic location with friends through smartphones equipped with GPS, search for interesting places as well as posting tips about existing locations. By allowing users to comment on locations, LBSNs increasingly have to deal with new forms of spammers, which aim at advertising unsolicited messages on tips about locations. Spammers may jeopardize the trust of users on the system, thus, compromising its success in promoting location-based social interactions. In spite of that, the available literature is very limited in providing a deep understanding of this problem. In this paper, we investigated the task of identifying different types of tip spam on a popular Brazilian LBSN system, namely Apontador. Based on a labeled collection of tips provided by Apontador as well as crawled information about users and locations, we identified three types of irregular tips, namely local marketing, pollution and, bad-mouthing. We leveraged our characterization study towards a classification approach able to differentiate these tips with high accuracy.-
Idioma: dc.languageen-
Direitos: dc.rightsO Periódico Information Sciences concede permissão para depósito do artigo no Repositório Institucional da UFOP. Número da licença: 3553111160571.-
Palavras-chave: dc.subjectLocation based social network-
Palavras-chave: dc.subjectSocial network-
Palavras-chave: dc.subjectTip spam-
Palavras-chave: dc.subjectTip analysis-
Título: dc.titlePollution, bad-mouthing, and local marketing : the underground of location-based social networks.-
Aparece nas coleções:Repositório Institucional - UFOP

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