LDA Topic Mining of Light Food Customer Reviews on the Meituan Platform

Miaojia Huang, Songqiao Wen, Manhua Jiang, Yuliang Yao

Research output: Chapter in Book/Conference paperConference paperpeer-review

2 Citations (Scopus)


Light food refers to healthy and nutritious food that has the characteristics of low calorie, low fat, and high fiber. Light food has been favored by the public, especially by the young generation in recent years. Moreover, affected by the COVID-19 epidemic, consumers’ awareness of a healthy diet has been improved to a certain extent. As both take-out and in-place orders for light food are growing rapidly, there are massive customer reviews left on the Meituan platform. However, massive, multi-dimensional unstructured data has not yet been fully explored. This research aims to explore the customers’ focal points and sentiment polarity of the overall comments and to investigate whether there exist differences of these two aspects before and after the COVID-19. A total of 6968 light food customer reviews on the Meituan platform were crawled and finally used for data analysis. This research first conducted the fine-grained sentiment analysis and classification of the light food customer reviews via the SnowNLP technique. In addition, LDA topic modeling was used to analyze positive and negative topics of customer reviews. The experimental results were visualized and the research showed that the SnowNLP technique and LDA topic modeling achieve high performance in extracting the customers’ sentiments and focal points, which provides theoretical and data support for light food businesses to improve customer service. This research contributes to the existing research on LDA modeling and light food customer review analysis. Several practical and feasible suggestions are further provided for managers in the light food industry.
Original languageEnglish
Title of host publicationInternational Conference on Data Mining and Big Data, DMBD 2021
EditorsYing Tan, Yuhui Shi, Albert Zomaya, Hongyang Yan, Jun Cai
PublisherSpringer Link
Number of pages14
ISBN (Print)9789811675010
Publication statusPublished - 30 Oct 2021
Externally publishedYes
Event6th International Conference on International Conference on Data Mining and Big Data - Guangzhou, China
Duration: 20 Oct 202122 Oct 2021

Publication series

NameCommunications in Computer and Information Science
Volume1454 CCIS
ISSN (Print)1865-0929
ISSN (Electronic)1865-0937


Conference6th International Conference on International Conference on Data Mining and Big Data
Abbreviated titleDMBD 2021


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