Sentiment Analysis Based on Product Review Data of Chinese Commerce Website of JD

DOI

10.2991/aebmr.k.200402.012How to use a DOI?

Keywords

sentiment analysis, machine learning, web spider

Abstract

With the popularity of the Internet and the development of e-commerce, online shopping has become more and more popular. Based on the commodity text comments of an e-commerce website, this paper uses machine learning method to analyze and mine the emotional direction of commodity comments. Finally, combining JIEBA and SNOWNLP, K-Folding Cross-Validation was used to obtain the final emotional score of the product review. The review scores displayed on e-commerce sites are unreliable. Moreover, the positive comment rate of the e-commerce platform is relatively high.

Copyright

© 2020, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Wenhua Song
AU  - Aiming Qin
AU  - Tiansheng Xu
PY  - 2020
DA  - 2020/04/06
TI  - Sentiment Analysis Based on Product Review Data of Chinese Commerce Website of JD
BT  - Proceedings of the 3rd International Conference on Advances in Management Science and Engineering (IC-AMSE 2020)
PB  - Atlantis Press
SP  - 67
EP  - 71
SN  - 2352-5428
UR  - https://doi.org/10.2991/aebmr.k.200402.012
DO  - 10.2991/aebmr.k.200402.012
ID  - Song2020
ER  -