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dc.contributor.author
Monteserin, Ariel José  
dc.contributor.author
Armentano, Marcelo Gabriel  
dc.date.available
2019-11-29T19:18:11Z  
dc.date.issued
2019-04  
dc.identifier.citation
Monteserin, Ariel José; Armentano, Marcelo Gabriel; Influence me! Predicting links to influential users; Springer; Information Retrieval; 22; 1-2; 4-2019; 32-54  
dc.identifier.issn
1386-4564  
dc.identifier.uri
http://hdl.handle.net/11336/90993  
dc.description.abstract
In addition to being in contact with friends, online social networks are commonly used as a source of information, suggestions and recommendations from members of the community. Whenever we accept a suggestion or perform any action because it was recommended by a “friend”, we are being influenced by him/her. For this reason, it is useful for users seeking for interesting information to identify and connect to this kind of influential users. In this context, we propose an approach to predict links to influential users. Compared to approaches that identify general influential users in a network, our approach seeks to identify users who might have some kind of influence to individual (target) users. To carry out this goal, we adapted an influence maximization algorithm to find new influential users from the set of current influential users of the target user. Moreover, we compared the results obtained with different metrics for link prediction and analyzed in which context these metrics obtained better results.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
Springer  
dc.rights
info:eu-repo/semantics/restrictedAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
LINK PREDICTION  
dc.subject
SOCIAL INFLUENCE  
dc.subject
SOCIAL NETWORKS  
dc.subject.classification
Ciencias de la Computación  
dc.subject.classification
Ciencias de la Computación e Información  
dc.subject.classification
CIENCIAS NATURALES Y EXACTAS  
dc.title
Influence me! Predicting links to influential users  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2019-10-21T20:04:15Z  
dc.identifier.eissn
1573-7659  
dc.journal.volume
22  
dc.journal.number
1-2  
dc.journal.pagination
32-54  
dc.journal.pais
Alemania  
dc.description.fil
Fil: Monteserin, Ariel José. 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.description.fil
Fil: Armentano, Marcelo Gabriel. 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.journal.title
Information Retrieval  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://link.springer.com/article/10.1007%2Fs10791-018-9335-0  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1007/s10791-018-9335-0