Evidence map›Paper›PMID 33920875›Full record

ArticleInternational journal of environmental research and public health2021

The Impact of COVID-19 on Consumers' Psychological Behavior Based on Data Mining for Online User Comments in the Catering Industry in China.

Chenyu Zhang, Jiayue Jiang, Hong Jin, Tinggui Chen

Abstract read
In one paragraph

Article in International journal of environmental research and public health, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

8 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Emerging Technologies for Investigating Food Consumer Behavior: A Systematic Review.Comprehensive reviews in food science and food safety · 2025
    Pooled it
  2. Article
  3. Attention and Sentiment of the Chinese Public toward a 3D Greening System Based on Sina Weibo.International journal of environmental research and public health · 2023
    Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Use of Respiratory Protection Devices by Medical Students during the COVID-19 Pandemic.International journal of environmental research and public health · 2021
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Chenyu ZhangSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.
Jiayue JiangSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.
Hong JinSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.
Tinggui ChenSchool of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou 310018, China.ORCID 0000-0001-6061-2517

Funding

National Social Science Foundation of China 20BTQ059
6 · The paper itself

Abstract

The outbreak of COVID-19 in late 2019 has had a huge impact on people's daily life. Many restaurant businesses have been greatly affected by it. Consumers' preferences for catering industry in China have changed, such as environmental hygiene, variety of dishes, and service methods. Therefore, the analysis of consumer preference differences and changes before and after the epidemic can not only provide emergency strategies for the catering industry but further improve the catering industry's ability to deal with public health emergencies. This paper takes five cities in China as representatives to explore the impact of COVID-19 on China's catering industry. Based on catering review data from August 2019 to April 2020, this paper first carries out Latent Dirichlet Allocation (LDA) topic analysis and SNOWNLP (A Python library for processing Chinese text) sentiment analysis. Then this paper compares the results of topic classification and sentiment analysis before and after the epidemic. Furthermore, differences and changes of consumer preferences are obtained and preferences of consumers under COVID-19 are analyzed and forecasted. The results of LDA thematic analysis before the outbreak of COVID-19 show that consumers tend to punch in cyber celebrity restaurants and pay more attention to the taste of dishes, whereas after it consumers pay more attention to the changes of dishes, dining environment as well as epidemic prevention. The number of packages and takeout was also increasing. However, the waiting time is constantly considered by consumers before and after COVID-19. Firstly, to our surprise, final outcome of emotional analysis showed that consumers' emotional state was more positive after the epidemic than before. COVID-19 has changed the lifestyle of consumers, consumption concepts, and consumption habits. Therefore, businesses also need to take positive and flexible measures to actively get feedback from consumers to adjust dishes and business methods. Secondly, the psychological attitude of catering consumers is relatively positive during the epidemic period, which indicates that consumers have great confidence in the recovery and development of the catering industry. Businesses can comply with consumers' psychology and combine consumption vouchers with restaurant discounts to promote consumers' consumption. Finally, the environment and service play more and more important effect on consumers' emotional scores at present, which indicates that dining state and comfortable mealtime environment are becoming increasingly valuable. Therefore, businesses need to improve service standards.

Indexed as

Consumer BehaviorCOVID-19ChinaData MiningHumansSARS-CoV-2consumers’ psychological behaviorCOVID-19data miningonline user comments

Identifiers

PMID33920875
PMCPMC8071308

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.