The three dimensions of social prominence

Diego Pennacchioli, Giulio Rossetti, Luca Pappalardo, Dino Pedreschi, Fosca Giannotti, Michele Coscia

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Résumé

One classic problem definition in social network analysis is the study of diffusion in networks, which enables us to tackle problems like favoring the adoption of positive technologies. Most of the attention has been turned to how to maximize the number of influenced nodes, but this approach misses the fact that different scenarios imply different diffusion dynamics, only slightly related to maximizing the number of nodes involved. In this paper we measure three different dimensions of social prominence: the Width, i.e. the ratio of neighbors influenced by a node; the Depth, i.e. the degrees of separation from a node to the nodes perceiving its prominence; and the Strength, i.e. the intensity of the prominence of a node. By defining a procedure to extract prominent users in complex networks, we detect associations between the three dimensions of social prominence and classical network statistics. We validate our results on a social network extracted from the Last.Fm music platform.

langue originaleAnglais
titreSocial Informatics - 5th International Conference, SocInfo 2013, Proceedings
Pages319-332
Nombre de pages14
Volume8238 LNCS
Les DOIs
Etat de la publicationPublié - 2013
Modification externeOui
Evénement5th International Conference on Social Informatics, SocInfo 2013 - Kyoto, Japon
Durée: 25 nov. 201327 nov. 2013

Série de publications

NomLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume8238 LNCS
ISSN (imprimé)03029743
ISSN (Electronique)16113349

Une conférence

Une conférence5th International Conference on Social Informatics, SocInfo 2013
Pays/TerritoireJapon
La villeKyoto
période25/11/1327/11/13

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