A categorized sentiment analysis of Chinese reviews by mining dependency in product features and opinions from blogs

Hung-Yu Kao, Zi Yu Lin

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

9 Citations (Scopus)

Abstract

In the past, there have been many documents focusing on English reviews for sentiment analysis. These contain abundant research results which extract features and opinions, identify semantic orientation, and associate features with opinions. Although this approach has performed well for English reviews, it is not as successful with Chinese reviews. In this paper, we aim to develop a sentiment analysis system that is suitable for Chinese reviews. This system would extract features that users are interested in and detect those opinions with semantic orientations that accord with the dependency of certain features and opinions in one specific category. We then present users with the integrated results. Our experiments show that the derived system can effectively measure the dependency between features and opinions. The prominent performance of review sentiment analysis also validates the applicability of the proposed method.

Original languageEnglish
Title of host publication2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Pages456-459
Number of pages4
DOIs
Publication statusPublished - 2010 Dec 13
Event2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010 - Toronto, ON, Canada
Duration: 2010 Aug 312010 Sep 3

Publication series

NameProceedings - 2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Volume1

Other

Other2010 IEEE/WIC/ACM International Conference on Web Intelligence, WI 2010
Country/TerritoryCanada
CityToronto, ON
Period10-08-3110-09-03

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence
  • Computer Networks and Communications
  • Software

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