Wisdom of the crowd: Incorporating social influence in recommendation models

Shang Shang, Pan Hui, Sanjeev R. Kulkarni, Paul W. Cuff

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

18 Scopus citations

Abstract

Recommendation systems have received considerable attention recently. However, most research has been focused on improving the performance of collaborative filtering (CF) techniques. Social networks, indispensably, provide us extra information on people's preferences, and should be considered and deployed to improve the quality of recommendations. In this paper, we propose two recommendation models, for individuals and for groups respectively, based on social contagion and social influence network theory. In the recommendation model for individuals, we improve the result of collaborative filtering prediction with social contagion outcome, which simulates the result of information cascade in the decision-making process. In the recommendation model for groups, we apply social influence network theory to take interpersonal influence into account to form a settled pattern of disagreement, and then aggregate opinions of group members. By introducing the concept of susceptibility and interpersonal influence, the settled rating results are flexible, and inclined to members whose ratings are "essential".

Original languageEnglish (US)
Title of host publicationProceedings - 2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011
Pages835-840
Number of pages6
DOIs
StatePublished - Dec 1 2011
Event2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011 - Tainan, Taiwan, Province of China
Duration: Dec 7 2011Dec 9 2011

Publication series

NameProceedings of the International Conference on Parallel and Distributed Systems - ICPADS
ISSN (Print)1521-9097

Other

Other2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011
CountryTaiwan, Province of China
CityTainan
Period12/7/1112/9/11

All Science Journal Classification (ASJC) codes

  • Hardware and Architecture

Keywords

  • Collaborative filtering
  • Recommendation model
  • Social influence

Fingerprint Dive into the research topics of 'Wisdom of the crowd: Incorporating social influence in recommendation models'. Together they form a unique fingerprint.

  • Cite this

    Shang, S., Hui, P., Kulkarni, S. R., & Cuff, P. W. (2011). Wisdom of the crowd: Incorporating social influence in recommendation models. In Proceedings - 2011 17th IEEE International Conference on Parallel and Distributed Systems, ICPADS 2011 (pp. 835-840). [6121365] (Proceedings of the International Conference on Parallel and Distributed Systems - ICPADS). https://doi.org/10.1109/ICPADS.2011.150