A community-based algorithm for deriving users’ profiles from egocentrics networks: experiment on Facebook and DBLP

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 using a community-based algorithm that is applied to a part of the user’s social network (egocentric network) and that derives a user social profile 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 individual-based techniques and the influence of structural measures (related to communities) on the quality of derived profiles. A second experiment on DBLP and the author’s social network Mendeley confirms the results obtained on Facebook and shows the influence of the density of egocentrics network on the quality of results.

[1]  Mohammad Ali Abbasi,et al.  Trust-Aware Recommender Systems , 2014 .

[2]  Shyhtsun Felix Wu,et al.  Analysis of user keyword similarity in online social networks , 2011, Social Network Analysis and Mining.

[3]  E. Goffman.  The Presentation of Self in Everyday Life , 1959 .

[4]  S. Borgatti,et al.  The centrality of groups and classes , 1999 .

[5]  Guillaume Cabanac,et al.  Accuracy of inter-researcher similarity measures based on topical and social clues , 2011, Scientometrics.

[6]  Hideaki Takeda,et al.  Using dynamic community detection to identify trends in user-generated content , 2012, Social Network Analysis and Mining.

[7]  Zhongfu Wu,et al.  Personalisation in web computing and informatics: Theories, techniques, applications, and future research , 2010, Inf. Syst. Frontiers.

[8]  Cong Wang,et al.  Social Relation Based Search Refinement: Let Your Friends Help You! , 2010, AMT.

[9]  Armelle Brun,et al.  Densifying a behavioral recommender system by social networks link prediction methods , 2011, Social Network Analysis and Mining.

[10]  Alessandro Micarelli,et al.  User Profiles for Personalized Information Access , 2007, The Adaptive Web.

[11]  Nadine Baptiste-Jessel,et al.  Visualizing the Evolution of Users' Profiles from Online Social Networks , 2010, 2010 International Conference on Advances in Social Networks Analysis and Mining.

[12]  R. K. Waldstein,et al.  Term relevance weights in on-line information retrieval , 1977, Inf. Process. Manag..

[13]  Rossano Schifanella,et al.  Link Creation and Profile Alignment in the aNobii Social Network , 2010, 2010 IEEE Second International Conference on Social Computing.

[14]  Peter V. Marsden,et al.  Egocentric and sociocentric measures of network centrality , 2002, Soc. Networks.

[15]  Ido Guy,et al.  Personalized social search based on the user's social network , 2009, CIKM.

[16]  M. A. Sasse,et al.  ’Knowing me, knowing you’ — Using profiles and social networking to improve recommender systems , 2006 .

[17]  Rashmi R. Sinha,et al.  Comparing Recommendations Made by Online Systems and Friends , 2001, DELOS.

[18]  Florence Sèdes,et al.  Visualizing the relevance of social ties in user profile modeling , 2012, Web Intell. Agent Syst..

[19]  Guillaume Chelius,et al.  Triangles to Capture Social Cohesion , 2011, 2011 IEEE Third Int'l Conference on Privacy, Security, Risk and Trust and 2011 IEEE Third Int'l Conference on Social Computing.

[20]  Gerhard Weikum,et al.  Exploiting social relations for query expansion and result ranking , 2008, 2008 IEEE 24th International Conference on Data Engineering Workshop.

[21]  Rémy Cazabet,et al.  Automated community detection on social networks: useful? efficient? asking the users , 2012, WI&C '12.

[22]  Rémy Cazabet,et al.  Detection of Overlapping Communities in Dynamical Social Networks , 2010, 2010 IEEE Second International Conference on Social Computing.

[23]  Michael Ley,et al.  DBLP - Some Lessons Learned , 2009, Proc. VLDB Endow..

[24]  Yiyu Yao,et al.  DBLP-SSE: A DBLP Search Support Engine , 2009, 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology.

[25]  Bart Selman,et al.  Referral Web: combining social networks and collaborative filtering , 1997, CACM.