A novel data-driven weighted sentiment analysis based on information entropy for perceived satisfaction
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DOI: 10.1016/j.jretconser.2022.103038
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Cited by:
- Xue, Zhebin & Li, Qing & Zeng, Xianyi, 2023. "Social media user behavior analysis applied to the fashion and apparel industry in the big data era," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
- Pang, Hua & Ruan, Yang, 2023. "Determining influences of information irrelevance, information overload and communication overload on WeChat discontinuance intention: The moderating role of exhaustion," Journal of Retailing and Consumer Services, Elsevier, vol. 72(C).
- Moradi, Masoud & Dass, Mayukh & Kumar, Piyush, 2023. "Differential effects of analytical versus emotional rhetorical style on review helpfulness," Journal of Business Research, Elsevier, vol. 154(C).
- Tian Tian & Liu Ze hui & Huang Zichen & Yubing Tang, 2024. "Enhancing Organizational Performance: Harnessing AI and NLP for User Feedback Analysis in Product Development," Papers 2405.04692, arXiv.org.
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Keywords
Perceived helpfulness prediction; Information entropy; Weighted analysis; Customer satisfaction; Supervised learning;All these keywords.
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