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dc.creatorTommasel, Antonela-
dc.creatorCorbellini, Alejandro-
dc.creatorGodoy, Daniela Lis-
dc.creatorSchiaffino, Silvia Noemi-
dc.date2018-09-05T20:38:13Z-
dc.date2018-09-05T20:38:13Z-
dc.date2016-05-
dc.date2018-09-05T16:11:13Z-
dc.date.accessioned2019-04-29T15:52:03Z-
dc.date.available2019-04-29T15:52:03Z-
dc.date.issued2016-05-
dc.identifierTommasel, Antonela; Corbellini, Alejandro; Godoy, Daniela Lis; Schiaffino, Silvia Noemi; Personality-aware followee recommendation algorithms: An empirical analysis; Pergamon-Elsevier Science Ltd; Engineering Applications Of Artificial Intelligence; 51; 5-2016; 24-36-
dc.identifier0952-1976-
dc.identifierhttp://hdl.handle.net/11336/58470-
dc.identifierCONICET Digital-
dc.identifierCONICET-
dc.identifier.urihttp://rodna.bn.gov.ar:8080/jspui/handle/bnmm/304113-
dc.descriptionAs the popularity of micro-blogging sites, expressed as the number of active users and volume of online activities, increases, the difficulty of deciding who to follow also increases. Such decision might not depend on a unique factor as users usually have several reasons for choosing whom to follow. However, most recommendation systems almost exclusively rely on only two traditional factors: graph topology and user-generated content, disregarding the effect of psychological and behavioural characteristics, such as personality, over the followee selection process. Due to its effect over people's reactions and interactions with other individuals, personality is considered as one of the primary factors that influence human behaviour. This study aims at assessing the impact of personality in the accurate prediction of followees, beyond simple topological and content-based factors. It analyses whether user personality could condition followee selection by combining personality traits with the most commonly used followee predictive factors. Results showed that an accurate appreciation of such predictive factors tied to a quantitative analysis of personality is crucial for guiding the search of potential followees, and thus, enhance recommendations.-
dc.descriptionFil: Tommasel, Antonela. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina-
dc.descriptionFil: Corbellini, Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina-
dc.descriptionFil: Godoy, Daniela Lis. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina-
dc.descriptionFil: Schiaffino, Silvia Noemi. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Tandil. Instituto Superior de Ingeniería del Software. Universidad Nacional del Centro de la Provincia de Buenos Aires. Instituto Superior de Ingeniería del Software; Argentina-
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dc.languageeng-
dc.publisherPergamon-Elsevier Science Ltd-
dc.relationinfo:eu-repo/semantics/altIdentifier/url/http://www.sciencedirect.com/science/article/pii/S0952197616000208-
dc.relationinfo:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1016/j.engappai.2016.01.016-
dc.rightsinfo:eu-repo/semantics/restrictedAccess-
dc.rightshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/-
dc.sourcereponame:CONICET Digital (CONICET)-
dc.sourceinstname:Consejo Nacional de Investigaciones Científicas y Técnicas-
dc.sourceinstacron:CONICET-
dc.subjectFOLLOWEE RECOMMENDATION-
dc.subjectHUMAN ASPECTS RECOMMENDATION-
dc.subjectPERSONALITY TRAITS-
dc.subjectTWITTER-
dc.subjectCiencias de la Computación-
dc.subjectCiencias de la Computación e Información-
dc.subjectCIENCIAS NATURALES Y EXACTAS-
dc.titlePersonality-aware followee recommendation algorithms: An empirical analysis-
dc.typeinfo:eu-repo/semantics/article-
dc.typeinfo:eu-repo/semantics/publishedVersion-
dc.typeinfo:ar-repo/semantics/articulo-
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