Segment-level joint topic-sentiment model for online review analysis

Qinjuan YANG, Yanghui RAO, Haoran XIE, Jiahai WANG, Fu Lee WANG, Wai Hong CHAN

Research output: Contribution to journalArticles

16 Citations (Scopus)

Abstract

With the rapid development of the Internet, an increasing number of users enjoy to shop online and express their reviews on the products and services. Analysis of these online reviews can not only help potential users make rational decisions when purchasing but also improves the quality of products and services. Hence, sentiment analysis for online reviews has become an important and meaningful research domain. Copyright © 2019 IEEE.
Original languageEnglish
Pages (from-to)43-50
JournalIEEE Intelligent Systems
Volume34
Issue number1
DOIs
Publication statusPublished - Jan 2019

Citation

Yang, Q., Rao, Y., Xie, H., Wang, J., Wang, F. L., & Chan, W. H. (2019). Segment-level joint topic-sentiment model for online review analysis. IEEE Intelligent Systems, 34(1), 43-50. doi: 10.1109/MIS.2019.2899142

Keywords

  • Sentiment analysis
  • Computational modeling
  • Internet
  • Motion pictures
  • Correlation
  • Analytical models
  • Feature extraction

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