DocumentCode :
592143
Title :
A Community Based Algorithm for Deriving Users´ Profiles from Egocentrics Networks
Author :
Tchuente, D. ; Canut, M. ; Baptiste-Jessel, N. ; Peninou, Andre ; Sedes, Florence
Author_Institution :
Inst. de Rech. en Inf. de Toulouse (IRIT), Paul Sabatier Univ., Toulouse, France
fYear :
2012
fDate :
26-29 Aug. 2012
Firstpage :
266
Lastpage :
273
Abstract :
Nowadays, social networks are more and more widely used as a solution for enriching users´ profiles in systems such as recommender systems or personalized systems. For an unknown user´s interest, the user´s social network can be a meaningful data source for deriving that interest. However, in the literature very few techniques are designed to meet this solution. Existing techniques usually focus on people individually selected in the user´s social network, and strongly depend on each author´s objective. To improve these techniques, we propose to use a community based algorithm that is applied to a part of the user´s social network (egocentric network) and that can be reused for any purpose (e.g. personalization, recommendation). We compute weighted user´s interests from these communities by considering their semantics (interests related to communities) and their structural measures (e.g. centrality measures) in the egocentric network graph. A first experiment conducted in Facebook demonstrates the usefulness of this technique compared to individuals based techniques, and the influence of structural measures (related to communities) on the quality of derived profiles. The results also raise the problem of users´ privacy in platforms such as online social networks. To enable users to better protect their privacy, these platforms should provide their users with a way to also make their friendlist private.
Keywords :
data privacy; graph theory; social networking (online); user interfaces; Facebook; centrality measure; community based algorithm; egocentric network; network graph; personalized system; recommender system; social network; user interest; user privacy; user profile delivery; Algorithm design and analysis; Communities; Facebook; Search engines; Semantics; Taxonomy; egocentric network; social network; social profiling; user modeling; user profile;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Social Networks Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference on
Conference_Location :
Istanbul
Print_ISBN :
978-1-4673-2497-7
Type :
conf
DOI :
10.1109/ASONAM.2012.53
Filename :
6425752
Link To Document :
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