Article

Recommendation in reciprocal and bipartite social networks: a case study of online dating

Authors:

Mo Yu,

Kang Zhao,

John Yen,

Derek KreagerAuthors Info & Claims

SBP'13: Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction

Pages 231 - 239

https://doi.org/10.1007/978-3-642-37210-0_25

Published: 02 April 2013 Publication History

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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.

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Yu MZhang XKreager DSubrahmanian VRokne JKumar RCaverlee JTong H(2016)New to online dating?Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192511(467-470)Online publication date: 18-Aug-2016
https://dl.acm.org/doi/10.5555/3192424.3192511

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Published In

SBP'13: Proceedings of the 6th international conference on Social Computing, Behavioral-Cultural Modeling and Prediction

April 2013

532 pages

ISBN:9783642372094

Editors:
Ariel M. Greenberg
Applied Physics Laboratory, Research and Exploratory Development Department, Johns Hopkins University, 11100 Johns Hopkins Road, Laurel, MD
,
William G. Kennedy
Center for Social Complexity, Department of Computational Social Science, Krasnow Institute for Advanced Study, George Mason University, 4400 University Drive, Fairfax, VA
,
Nathan D. Bos
Applied Physics Laboratory, Research and Exploratory Development Department, Johns Hopkins University, 11100 Johns Hopkins Road, Laurel, MD

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Springer-Verlag

Berlin, Heidelberg

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Published: 02 April 2013

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Yu MZhang XKreager DSubrahmanian VRokne JKumar RCaverlee JTong H(2016)New to online dating?Proceedings of the 2016 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining10.5555/3192424.3192511(467-470)Online publication date: 18-Aug-2016
https://dl.acm.org/doi/10.5555/3192424.3192511

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Reciprocal recommender system for online dating

Recommending people to people: the nature of reciprocal recommenders with a case study in online dating

Reciprocal Recommendation: Matching Users with the Right Users

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