Evidence map›Paper›PMID 32834635›Full record

ArticleChaos, solitons, and fractals2020

Analysis of spatiotemporal characteristics of big data on social media sentiment with COVID-19 epidemic topics.

Bangren Zhu, Xinqi Zheng, Haiyan Liu, Jiayang Li, Peipei Wang

Open access · greenAbstract read
In one paragraph

Article in Chaos, solitons, and fractals, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
41citing papers in PubMed, 1 pooled it
164.8field-weighted citation impact, top 1% of its field
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

41 citing papers in PubMed, 1 synthesis or guideline pooled it, 145 citations in OpenAlex.

  1. When Infodemic Meets Epidemic: Systematic Literature Review.JMIR public health and surveillance · 2025
    Pooled it
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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

5 authors at 1 institution in 1 country.

Bangren ZhuSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.
Xinqi ZhengSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.
Haiyan LiuSchool of Economic and Management, China University of Geosciences, Beijing 100083, China.
Jiayang LiSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.
Peipei WangSchool of Information Engineering, China University of Geosciences, Beijing 100083, China.
China University of Geosciences (Beijing) · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

COVID-19 blocked Wuhan in China, which was sealed off on Chinese New Year's Eve. During this period, the research on the relevant topics of COVID-19 and emotional expressions published on social media can provide decision support for the management and control of large-scale public health events. The research assisted the analysis of microblog text topics with the help of the LDA model, and obtained 8 topics ("origin", "host", "organization", "quarantine measures", "role models", "education", "economic", "rumor") and 28 interactive topics. Obtain data through crawler tools, with the help of big data technology, social media topics and emotional change characteristics are analyzed from spatiotemporal perspectives. The results show that: (1) "Double peaks" feature appears in the epidemic topic search curve. Weibo on the topic of the epidemic gradually reduced after January 24. However, the proportion of epidemic topic searches has gradually increased, and a "double peaks" phenomenon appeared within a week; (2) The topic changes with time and the fluctuation of the topic discussion rate gradually weakens. The number of texts on different topics and interactive topics changes with time. At the same time, the discussion rate of epidemic topics gradually weakens; (3) The political and economic center is an area where social media is highly concerned. The areas formed by Beijing, Shanghai, Guangdong, Sichuan and Hubei have published more microblog texts. The spatial division of the number of Weibo social media texts has a high correlation with the economic zone division; (4) The existence of the topic of "rumor" will enable people to have more communication and discussion. The interactive topics of "rumors" always have higher topic popularity and low emotion text expressions. Through the analysis of media information, it helps relevant decision makers to grasp social media topics from spatiotemporal characteristics, so that relevant departments can accurately grasp the public's subjective ideas and emotional expressions, and provide decision support for macro-control response strategies and measures and risk communication.

Indexed as

COVID-19Epidemic topicsSocial mediaSpatiotemporal characteristics

Identifiers

PMID32834635
PMCPMC7367019
OpenAlexW3042694964

What OpenQuestion holds

Textmetadata
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.