Exploring and inferring user-user pseudo-friendship for sentiment analysis with heterogeneous networks

Hongbo Deng, Jiawei Han, Hao Li, Heng Ji, Hongning Wang, Yue Lu

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

Abstract

With the development of social media and social networks, user-generated content, like forums, blogs and comments, are not only getting richer, but also ubiquitously interconnected with many other objects and entities, forming a heterogeneous information network between them. Sentiment analysis on such kinds of data can no longer ignore the information network, since it carries a lot of rich and valuable information, explicitly or implicitly, where some of them can be observed while others are not. In this paper, we propose a novel information network-based framework which can infer hidden similarity and dissimilarity between users by exploring similar and opposite opinions, so as to improve postlevel and user-level sentiment classification in the same time. More specifically, we develop a new meta path-based measure for inferring pseudo-friendship as well as dissimilarity between users, and propose a semi-supervised refining model by encoding similarity and dissimilarity from both user-level and post-level relations. We extensively evaluate the proposed approach and compare with several state-of-the-art techniques on two real-world forum datasets. Experimental results show that our proposed model with 10.5% labeled samples can achieve better performance than a traditional supervised model trained on 61.7% data samples.

Original languageEnglish (US)
Title of host publicationProceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013
EditorsSrinivasan Parthasarathy, Joydeep Ghosh, Zhi-Hua Zhou, Jennifer Dy, Zoran Obradovic, Chandrika Kamath
PublisherSiam Society
Pages378-386
Number of pages9
ISBN (Electronic)9781611972627
StatePublished - Jan 1 2013
EventSIAM International Conference on Data Mining, SDM 2013 - Austin, United States
Duration: May 2 2013May 4 2013

Publication series

NameProceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013

Other

OtherSIAM International Conference on Data Mining, SDM 2013
CountryUnited States
CityAustin
Period5/2/135/4/13

ASJC Scopus subject areas

  • Computer Science Applications
  • Software
  • Theoretical Computer Science
  • Information Systems
  • Signal Processing

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  • Cite this

    Deng, H., Han, J., Li, H., Ji, H., Wang, H., & Lu, Y. (2013). Exploring and inferring user-user pseudo-friendship for sentiment analysis with heterogeneous networks. In S. Parthasarathy, J. Ghosh, Z-H. Zhou, J. Dy, Z. Obradovic, & C. Kamath (Eds.), Proceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013 (pp. 378-386). (Proceedings of the 2013 SIAM International Conference on Data Mining, SDM 2013). Siam Society.