Evidence map›Paper›PMID 38476974›Full record

ArticleDigital health

Opinion leaders and crisis communication during the COVID-19 pandemic: A study of theme evolution and emotional impact on Twitter.

Yan Wang, Shuang Yang, Xinying An

Open access · goldAbstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
1.9field-weighted citation impact, top 16% 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

1 citing paper in PubMed, 2 citations in OpenAlex.

  1. 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

3 authors at 1 institution in 1 country.

Yan WangDepartment of Medical Science and Technology Evaluation. Institute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.ORCID https://orcid.org/0000-0003-3581-5210
Shuang YangDepartment of Medical Science and Technology Evaluation. Institute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
Xinying AnDepartment of Medical Science and Technology Evaluation. Institute of Medical Information, Chinese Academy of Medical Sciences/Peking Union Medical College, Beijing, China.
Chinese Academy of Medical Sciences & Peking Union Medical College · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study uses Twitter data from the early stages of the pandemic to analyze the evolution of topics during different time periods and attempts to investigate the content and emotional impact of opinion leaders on public opinion evolution under different themes, in order to understand their role in shaping public discourse and emotions. Divide the life cycle into three stages; NLTK emotional analysis and dynamic topic models (DTMs) are employed to extract and analyze topic words. The results showed that there were significant differences between opinion leaders and followers in terms of hot topics and their evolution trends: (1) In terms of hot topics, opinion leaders have always been paying attention to measures and methods aimed at the public, while followers usually have persist in seeking information and dissatisfaction. (2) In terms of identifying and evolving hot topics, opinion leaders have shifted from the impact of the epidemic on individuals and resources to government responses and policies, while followers are more inclined to express people's growing concerns and dissatisfaction with crisis management. The content of opinion leaders has a significant relationship with evolving public opinion, highlighting the importance of understanding their role in crisis communication. Opinion leaders are also categorized into five types, each with different audience sizes, contents, emotions, and network structures, and they impact public opinion differently. This study identifies and analyzes the characteristics and impact mechanisms of opinion leaders in crisis communication. It hopes to contribute to understanding crisis communication dynamics in the digital era and provide insights into effective communication strategies during crises.

Indexed as

COVID-19Crisis communicationopinion leaderstheme evolution

Identifiers

PMID38476974
PMCPMC10929030
OpenAlexW4392665705

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.