Crowdsourcing recommendations from social sentiment

Yusheng Xie*, Yu Cheng, Daniel Honbo, Kunpeng Zhang, Ankit Agrawal, Alok Nidhi Choudhary

*Corresponding author for this work

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

1 Scopus citations

Abstract

In this paper, we investigate an innovative recommendation system by incorporating relevant social opinion and sentiment information. Our recommendation system, a powerful application of social sentiment analysis, differs from many existing models, which investigate the situation where the social network itself is structured to work with the product ranking and is specially built inside an e-commerce website. In contrast, our proposed system focuses on constructing and inferring product recommendations from external social network services (SNS) such as Facebook. In our system, we process product features in a finite-dimensional polynomial linear space. Additional components of our proposed system include an asymmetric similarity measurement and an asymmetric advantage measurement. We also show that our definitions for the two measurements include specific properties that reduce the computational overhead in the experiments. An important aspect of our modeling is to incorporate user-generated high-level semantic sentiment in the analysis. We apply our models to real time data and observe promising results for not only product recommendation but also job recommendation.

Original languageEnglish (US)
Title of host publicationProceedings of the 1st International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2012 - Held in Conjunction with SIGKDD 2012
DOIs
StatePublished - Sep 14 2012
Event1st International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2012 - Held in Conjunction with SIGKDD 2012 - Beijing, China
Duration: Aug 12 2012Aug 12 2012

Publication series

NameProceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

Other

Other1st International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2012 - Held in Conjunction with SIGKDD 2012
CountryChina
CityBeijing
Period8/12/128/12/12

Keywords

  • business intelligence
  • crowdsourcing

ASJC Scopus subject areas

  • Software
  • Information Systems

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  • Cite this

    Xie, Y., Cheng, Y., Honbo, D., Zhang, K., Agrawal, A., & Choudhary, A. N. (2012). Crowdsourcing recommendations from social sentiment. In Proceedings of the 1st International Workshop on Issues of Sentiment Discovery and Opinion Mining, WISDOM 2012 - Held in Conjunction with SIGKDD 2012 (Proceedings of the ACM SIGKDD International Conference on Knowledge Discovery and Data Mining). https://doi.org/10.1145/2346676.2346685