Research Article
Text Mining and Analysis of Meituan User Review Text
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@INPROCEEDINGS{10.1007/978-3-030-62483-5_16, author={Yong-juan Wang and Guang-hua Yu and Li-nan Sun and Pei-ge Liu}, title={Text Mining and Analysis of Meituan User Review Text}, proceedings={Green Energy and Networking. 7th EAI International Conference, GreeNets 2020, Harbin, China, June 27-28, 2020, Proceedings}, proceedings_a={GREENETS}, year={2020}, month={11}, keywords={Online user reviews Text segmentation Keyword extraction}, doi={10.1007/978-3-030-62483-5_16} }- Yong-juan Wang
Guang-hua Yu
Li-nan Sun
Pei-ge Liu
Year: 2020
Text Mining and Analysis of Meituan User Review Text
GREENETS
Springer
DOI: 10.1007/978-3-030-62483-5_16
Abstract
Based on the current situation of the market, this paper obtains related data of online user reviews on Meituan the online food delivery platform by soft wares and implements preprocessing and mining by language correlation function, and finally draws a conclusion that judging from the mining results of the featured words and the emotions in the reviews, the Meituan platform and its food delivery service have been evaluated by users as being cheap, economical, convenient and fast, and the key elements that users concern regarding to the merchant rating are the merchant’s attitude, the delivery man’s attitude, the food taste and the food security respectively.
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