Evidence map›Paper›PMID 38843521›Full record

ArticleJournal of medical Internet research2024

News Coverage of the COVID-19 Pandemic on Social Media and the Public's Negative Emotions: Computational Study.

Hanjing Wang, Yupeng Li, Xuan Ning

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

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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

3 authors.

Hanjing Wang *School of Communication, Hong Kong Baptist University, Hong Kong, China (Hong Kong).ORCID 0000-0001-9597-6054
Yupeng Li *Department of Interactive Media, Hong Kong Baptist University, Hong Kong, China (Hong Kong).ORCID 0000-0001-9652-3321
Xuan NingDepartment of Social Sciences, Beijing Normal University-Hong Kong Baptist University United International College, Zhuhai, China.ORCID 0000-0003-1459-2847

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundSocial media has become an increasingly popular and critical tool for users to digest diverse information and express their perceptions and attitudes. While most studies endeavor to delineate the emotional responses of social media users, there is limited research exploring the factors associated with the emergence of emotions, particularly negative ones, during news consumption.

objectiveWe aim to first depict the web coverage by news organizations on social media and then explore the crucial elements of news coverage that trigger the public's negative emotions. Our findings can act as a reference for responsible parties and news organizations in times of crisis.

methodsWe collected 23,705 Facebook posts with 1,019,317 comments from the public pages of representative news organizations in Hong Kong. We used text mining techniques, such as topic models and Bidirectional Encoder Representations from Transformers, to analyze news components and public reactions. Beyond descriptive analysis, we used regression models to shed light on how news coverage on social media is associated with the public's negative emotional responses.

resultsOur results suggest that occurrences of issues regarding pandemic situations, antipandemic measures, and supportive actions are likely to reduce the public's negative emotions, while comments on the posts mentioning the central government and the Government of Hong Kong reveal more negativeness. Negative and neutral media tones can alleviate the rage and interact with the subjects and issues in the news to affect users' negative emotions. Post length is found to have a curvilinear relationship with users' negative emotions.

conclusionsThis study sheds light on the impacts of various components of news coverage (issues, subjects, media tone, and length) on social media on the public's negative emotions (anger, fear, and sadness). Our comprehensive analysis provides a reference framework for efficient crisis communication for similar pandemics at present or in the future. This research, although first extending the analysis between the components of news coverage and negative user emotions to the scenario of social media, echoes previous studies drawn from traditional media and its derivatives, such as web newspapers. Although the era of COVID-19 pandemic gradually brings down the curtain, the commonality of this research and previous studies also contributes to establishing a clearer territory in the field of health crises.

Indexed as

COVID-19EmotionsSocial MediaData MiningHong KongHumansMass MediaPandemicsSARS-CoV-2COVID-19emotionsFacebooksocial mediaweb news coverage

Identifiers

PMID38843521
PMCPMC11190626

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.