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BFF: A tool for eliciting tie strength and user communities in social networking services

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BFF: A tool for eliciting tie strength and user communities in social networking services

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dc.contributor.author López Fogués, Ricard es_ES
dc.contributor.author Such Aparicio, José Miguel es_ES
dc.contributor.author Espinosa Minguet, Agustín Rafael es_ES
dc.contributor.author García-Fornes, A es_ES
dc.date.accessioned 2015-05-26T10:17:29Z
dc.date.available 2015-05-26T10:17:29Z
dc.date.issued 2014-04
dc.identifier.issn 1387-3326
dc.identifier.uri http://hdl.handle.net/10251/50752
dc.description The final publication is available at Springer via http://dx.doi.org/ 10.1007/s10796-013-9453-6 es_ES
dc.description.abstract The use of social networking services (SNSs) such as Facebook has explosively grown in the last few years. Users see these SNSs as useful tools to find friends and interact with them. Moreover, SNSs allow their users to share photos, videos, and express their thoughts and feelings. However, users are usually concerned about their privacy when using SNSs. This is because the public image of a subject can be affected by photos or comments posted on a social network. In this way, recent studies demonstrate that users are demanding better mechanisms to protect their privacy. An appropriate approximation to solve this could be a privacy assistant software agent that automatically suggests a privacy policy for any item to be shared on a SNS. The first step for developing such an agent is to be able to elicit meaningful information that can lead to accurate privacy policy predictions. In particular, the information needed is user communities and the strength of users' relationships, which, as suggested by recent empirical evidence, are the most important factors that drive disclosure in SNSs. Given the number of friends that users can have and the number of communities they may be involved on, it is infeasible that users are able to provide this information without the whole eliciting process becoming confusing and time consuming. In this work, we present a tool called Best Friend Forever (BFF) that automatically classifies the friends of a user in communities and assigns a value to the strength of the relationship ties to each one. We also present an experimental evaluation involving 38 subjects that showed that BFF can significantly alleviate the burden of eliciting communities and relationship strength. es_ES
dc.description.sponsorship This work has been partially supported by CONSOLIDER-INGENIO 2010 under grant CSD2007-00022, and TIN 2008-04446 and PROMETEO II/2013/019 projects. This article has been developed as a result of a mobility stay funded by the Erasmus Mundus Programme of the European Comission under the Transatlantic Partnership for Excellence in Engineering - TEE Project. en_EN
dc.language Inglés es_ES
dc.publisher Springer Verlag (Germany) es_ES
dc.relation CONSOLIDER-INGENIO [CSD2007-00022] [TIN 2008-04446] es_ES
dc.relation PROMETEO [ II/2013/019] es_ES
dc.relation Erasmus Mundus Programme of the European Comission under the Transatlantic Partnership for Excellence in Engineering - TEE Project es_ES
dc.relation.ispartof Information Systems Frontiers es_ES
dc.rights Reserva de todos los derechos es_ES
dc.subject Information retrieval es_ES
dc.subject Social network es_ES
dc.subject Social media es_ES
dc.subject Privacy es_ES
dc.subject Tie strength es_ES
dc.subject.classification LENGUAJES Y SISTEMAS INFORMATICOS es_ES
dc.title BFF: A tool for eliciting tie strength and user communities in social networking services es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.1007/s10796-013-9453-6
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Sistemas Informáticos y Computación - Departament de Sistemes Informàtics i Computació es_ES
dc.description.bibliographicCitation López Fogués, R.; Such Aparicio, JM.; Espinosa Minguet, AR.; García-Fornes, A. (2014). BFF: A tool for eliciting tie strength and user communities in social networking services. Information Systems Frontiers. 16:225-237. doi:10.1007/s10796-013-9453-6 es_ES
dc.description.accrualMethod Senia es_ES
dc.relation.publisherversion http://link.springer.com/article/10.1007/s10796-013-9453-6 es_ES
dc.description.upvformatpinicio 225 es_ES
dc.description.upvformatpfin 237 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 16 es_ES
dc.relation.senia 258051
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