Sentiment detection and visualization of Chinese micro-blog

Zhitao Wang, Zhiwen Yu, Liming (Luke) Chen, Bin Guo

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

7 Citations (Scopus)

Abstract

Micro-blog has been increasingly used for the public to express their opinions, and for organisations to detect public sentiment about social events. In contrast to the effort and progress made in English-based micro-blog analysis, research on Chinese micro-blog received relatively little attention. In this paper we examine and identify the key problems of this field, focusing particularly on the characteristics of innovative words, emoticon elements and hierarchical structure of Chinese “Weibo”. Based on the analysis we propose and develop associated theoretical and technological methods to address these problems. These include the development of new sentiment word mining method based on three wording standards and point-wise metrics, a rule set model for analyzing sentiment features of different linguistic components, and the corresponding methodology for calculating sentiment on multi-granularity considering emoticon elements. We use original Chinese tweets from a dataset of Sina Weibo to test and evaluate our new word discovery and sentiment detection methods. Initial results show that our new diction can improve sentiment detection, and demonstrate that our multi-level rule set method is more effective by giving 10.2% and 1.5% higher average accuracy than two existing methods for Chinese micro-blog sentiment analysis. In addition, we exploit visualisation techniques to study the relationships between online sentiment and real life, which can help depict the correlation between public emotions and events.
Original languageEnglish
Title of host publication 2014 International Conference on Data Science and Advanced Analytics (DSAA)
Place of PublicationShanghai, China
PublisherIEEE Xplore
Pages251-257
Number of pages7
ISBN (Print)978-1-4799-6991-3
DOIs
Publication statusPublished (in print/issue) - 12 Oct 2014
Event2014 International Conference on Data Science and Advanced Analytics (DSAA) - Shanghai, China
Duration: 30 Oct 20141 Nov 2014

Conference

Conference2014 International Conference on Data Science and Advanced Analytics (DSAA)
Period30/10/141/11/14

Keywords

  • Vectors
  • Mood
  • Feature extraction
  • pragmatics
  • Sentiment anlaysis
  • Twitter
  • silicon

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