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Journal of Electrical and Computer Engineering
Volume 2016, Article ID 7282913, 6 pages
http://dx.doi.org/10.1155/2016/7282913
Research Article

Microblog Sentiment Orientation Detection Using User Interactive Relationship

Xi’an University of Science and Technology, Xi’an 710054, China

Received 26 November 2015; Accepted 16 February 2016

Academic Editor: Jiang Zhu

Copyright © 2016 Liang Wang et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

The development and popularity of microblog have made sentiment analysis of tweets and Weibo an important research field. However, the characteristics of microblog message pose challenge for the sentiment analysis and mining. The existing approaches mostly focus on the message content and context information. In this paper, we propose a novel microblog sentiment analysis framework by incorporating the social interactive relationship factor in the content-based approach. By exploring the interactive relationship on social network based on posted messages, we build social interactive model to represent the opposition or acceptation behavior. Based on the interactive relationship model, the sentiment of microblog message with sparse emotion terms can be deduced and identified, and the sentiment uncertainty can be alleviated to some extent. Afterwards, we transform the classification problem into an optimization problem. Experimental results on Weibo data set indicate that the proposed method can outperform the baseline methods.