Evidence map›Paper›PMID 38785880›Full record

ArticleBehavioral sciences (Basel, Switzerland)2024

Digital Mass Hysteria during Pandemic? A Study of Twitter Communication Patterns in the US during the Stages of COVID-19 Vaccination.

Dohyo Jeong, Jessi Hanson-DeFusco, Dohyeong Kim, Chang-Kil Lee

Abstract read
In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing 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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Dohyo JeongSchool of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.
Jessi Hanson-DeFuscoSchool of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0002-1265-8403
Dohyeong KimSchool of Economic, Political and Policy Sciences, University of Texas at Dallas, Richardson, TX 75080, USA.ORCID 0000-0002-1428-1451
Chang-Kil LeeDepartment of Urban Policy and Administration, Incheon National University, Incheon 22012, Republic of Korea.

Funding

Incheon National University International Cooperative Research Grant 2022
6 · The paper itself

Abstract

This study examined the public's sentiments about vaccines by analyzing Twitter data during the CDC's vaccination management planning stage in the United States. Sentiment scores were assigned to each tweet using a sentiment dictionary and the sentiment changes were analyzed over 52 weeks from November 2020 to November 2021. An interrupted time series model was used to analyze the difference in sentiment, which revealed that there was a shift. Initially, overall sentiments were negative but became positive as the stage of general vaccine supply approached. However, negative sentiments sharply rose when the vaccine supply transitioned to the phase of universalization. The results identified two dominant strategic action fields for vaccines providing polarized messages on Twitter and the negative trend was strong for most of the period. The findings highlight the importance of managing strategic action fields on social networks to prevent mass hysteria during vaccine policy implementation. This study stresses the significance of effectively managing strategic action fields on social media platforms to prevent mass hysteria while implementing vaccine policies.

Indexed as

COVID-19interrupted time seriessentiment analysisstrategic action fieldsvaccination

Identifiers

PMID38785880
PMCPMC11117666

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.