Recommendation in reciprocal and bipartite social networks - A case study of online dating

Mo Yu, Kang Zhao, John Yen, Derek Kreager

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

Abstract

Many social networks in our daily life are bipartite networks that are built on reciprocity. How can we recommend users/friends to a user, so that the user is interested in and attractive to recommended users? In this research, we propose a new collaborative filtering model to improve user recommendations in reciprocal and bipartite social networks. The model considers a user's "taste" in picking others and "attractiveness" in being picked by others. A case study of an online dating network shows that the new model outperforms a baseline collaborative filtering model on recommending both initial contacts and reciprocal contacts.

Original languageEnglish (US)
Title of host publicationSocial Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings
Pages231-239
Number of pages9
DOIs
StatePublished - Mar 14 2013
Event6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013 - Washington, DC, United States
Duration: Apr 2 2013Apr 5 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7812 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other6th International Conference on Social Computing, Behavioral-Cultural Modeling and Prediction, SBP 2013
CountryUnited States
CityWashington, DC
Period4/2/134/5/13

All Science Journal Classification (ASJC) codes

  • Theoretical Computer Science
  • Computer Science(all)

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    Yu, M., Zhao, K., Yen, J., & Kreager, D. (2013). Recommendation in reciprocal and bipartite social networks - A case study of online dating. In Social Computing, Behavioral-Cultural Modeling and Prediction - 6th International Conference, SBP 2013, Proceedings (pp. 231-239). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7812 LNCS). https://doi.org/10.1007/978-3-642-37210-0_25