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 language | English |
|---|---|
| Pages (from-to) | 43-50 |
| Journal | IEEE Intelligent Systems |
| Volume | 34 |
| Issue number | 1 |
| DOIs | |
| Publication status | Published - 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.2019.2899142Keywords
- Sentiment analysis
- Computational modeling
- Internet
- Motion pictures
- Correlation
- Analytical models
- Feature extraction