E-commerce review sentiment score prediction considering misspelled words: a deep learning approach
Author:
Publisher
Springer Science and Business Media LLC
Subject
Human-Computer Interaction,Economics, Econometrics and Finance (miscellaneous)
Link
https://link.springer.com/content/pdf/10.1007/s10660-022-09582-4.pdf
Reference43 articles.
1. Singh, J. P., Irani, S., Rana, N. P., Dwivedi, Y. K., Saumya, S., & Roy, P. K. (2017). Predicting the ôhelpfulnessö of online consumer reviews. Journal of Business Research, 70, 346–355.
2. Saumya, S., Singh, J. P., & Dwivedi, Y. K. (2020). Predicting the helpfulness score of online reviews using convolutional neural network. Soft Computing, 24(15), 10–11.
3. Saumya, S., Singh, J. P., Baabdullah, A. M., Rana, N. P., & Dwivedi, Y. K. (2018). Ranking online consumer reviews. Electronic Commerce Research and Applications, 29, 78–89.
4. Wang, Y., Wang, J., & Yao, T. (2019). What makes a helpful online review? A meta-analysis of review characteristics. Electronic Commerce Research, 19(2), 257–284.
5. Syamala, M., & Nalini, N. J. (2020). A filter based improved decision tree sentiment classification model for real-time amazon product review data. International Journal of Intelligent Engineering and Systems, 13(1), 191–202.
Cited by 4 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献
1. E-Commerce Review Sentiment Analysis and Purchase Intention Prediction Based on Deep Learning Technology;Journal of Organizational and End User Computing;2023-12-29
2. How the metaverse influences marketing and competitive advantage of retailers: predictions and key marketing research priorities;Electronic Commerce Research;2023-12-08
3. A Brief Survey of Machine Learning and Deep Learning Techniques for E-Commerce Research;Journal of Theoretical and Applied Electronic Commerce Research;2023-12-04
4. Metaverse-related perceptions and sentiments on Twitter: evidence from text mining and network analysis;Electronic Commerce Research;2023-08-13
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370
www.globalauthorid.com
TOP
Copyright © 2019-2024 北京同舟云网络信息技术有限公司 京公网安备11010802033243号 京ICP备18003416号-3