Evidence map›Paper›PMID 34406961›Full record

ArticleJournal of medical Internet research2021

Framing of and Attention to COVID-19 on Twitter: Thematic Analysis of Hashtags.

Iman Tahamtan, Devendra Potnis, Ehsan Mohammadi, Laura E Miller, Vandana Singh

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
–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. Article
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  3. A National Discussion of COVID-19 on Twitter.Journal of the Association of Medical Microbiology and Infectious Disease Canada = Journal officiel de l'Association pour la microbiologie medicale et l'infectiologie Canada · 2024
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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.

Iman Tahamtan *School of Information Sciences, The University of Tennessee, Knoxville, TN, United States.ORCID 0000-0001-7750-0183
Devendra PotnisSchool of Information Sciences, The University of Tennessee, Knoxville, TN, United States.ORCID 0000-0003-2507-8157
Ehsan MohammadiSchool of Information Science, The University of South Carolina, Columbia, SC, United States.ORCID 0000-0003-3481-6991
Laura E MillerSchool of Communication Studies, The University of Tennessee, Knoxville, TN, United States.ORCID 0000-0002-4488-8051
Vandana SinghSchool of Information Sciences, The University of Tennessee, Knoxville, TN, United States.ORCID 0000-0002-9800-0505

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundAlthough past research has focused on COVID-19-related frames in the news media, such research may not accurately capture and represent the perspectives of people from diverse backgrounds. Additionally, research on the public attention to COVID-19 as reflected through frames on social media is scarce.

objectiveThis study identified the frames about the COVID-19 pandemic in the public discourse on Twitter, which voices diverse opinions. This study also investigated the amount of public attention to those frames on Twitter.

methodsWe collected 22 trending hashtags related to COVID-19 in the United States and 694,582 tweets written in English containing these hashtags in March 2020 and analyzed them via thematic analysis. Public attention to these frames was measured by evaluating the amount of public engagement with frames and public adoption of those frames.

resultsWe identified 9 frames including "public health guidelines," "quarantine life," "solidarity," "evidence and facts," "call for action," "politics," "post-pandemic life," "shortage panic," and "conflict." Results showed that some frames such as "call for action" are more appealing than others during a global pandemic, receiving greater public adoption and engagement. The "call for action" frame had the highest engagement score, followed by "conflict" and "evidence and facts." Additionally, "post-pandemic life" had the highest adoption score, followed by "call for action" and "shortage panic." The findings indicated that the frequency of a frame on social media does not necessarily mean greater public adoption of or engagement with the frame.

conclusionsThis study contributes to framing theory and research by demonstrating how trending hashtags can be used as new user-generated data to identify frames on social media. This study concludes that the identified frames such as "quarantine life" and "conflict" and themes such as "isolation" and "toilet paper panic" represent the consequences of the COVID-19 pandemic. The consequences could be (1) exclusively related to COVID-19, such as hand hygiene or isolation; (2) related to any health crisis such as social support of vulnerable groups; and (3) generic that are irrespective of COVID-19, such as homeschooling or remote working.

Indexed as

COVID-19Social MediaHumansPandemicsPublic HealthSARS-CoV-2United StatesCOVID-19engagementframingpublic attentionpublic healthpublic opinionsocial mediathematic analysisTwitter

Identifiers

PMID34406961
PMCPMC8437404

What OpenQuestion holds

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Registered trials

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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.