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: Journal Publications › Journal Article (refereed)

17 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.

Original languageEnglish
Article number8667097
Pages (from-to)43-50
Number of pages8
JournalIEEE Intelligent Systems
Volume34
Issue number1
DOIs
Publication statusPublished - Jan 2019
Externally publishedYes

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    • Research Output

    • 17 Scopus Citations
    • 1 Erratum

    Erratum : Segment-Level Joint Topic-Sentiment Model for Online Review Analysis (IEEE Intelligent Systems (2019) 34:1 (43-50) DOI: 10.1109/MIS.2019.2899142)

    XIE, H., 1 Mar 2019, IEEE Intelligent Systems, 34, 2 1 p.

    Research output: Other Publications › Erratum

    • Cite this

    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. [8667097]. https://doi.org/10.1109/MIS.2019.2899142