Emotional Analysis of E-Commerce Online Comment Data

DOI

10.2991/assehr.k.191221.038How to use a DOI?

Keywords

LDA Topic Model, Python Programming, Online Review of E-Commerce, Emotional Analysis

Abstract

Introducing text emotion analysis into e-commerce online comment data can judge the emotional tendency of e-commerce online comments. At the same time, the application of Python Jieba participle and LDA topic model enables more detailed understanding of the emotional changes in online comments of e-commerce. Taking product reviews of Midea water heater on JD.com as an example, the empirical analysis shows that the online product review, by introducing text sentiment analysis, determines the consumer emotion tendency, which can help with the electric business improvement project for merchants to provide accurate marketing, set up new businesses evaluation way, dynamically monitor customer emotional tendency, and timely grasp the emotional trend of E-commerce industry.

Copyright

© 2019, 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  - Lili Jin
PY  - 2019
DA  - 2019/12/30
TI  - Emotional Analysis of E-Commerce Online Comment Data
BT  - Proceedings of the 2019 3rd International Conference on Education, Economics and Management Research (ICEEMR 2019)
PB  - Atlantis Press
SP  - 159
EP  - 162
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.191221.038
DO  - 10.2991/assehr.k.191221.038
ID  - Jin2019
ER  -