Evidence map›Paper›PMID 39611080›Full record

ArticleInternational journal of public health2024

Proposing a Conceptual Framework: Social Media Infodemic Listening for Public Health Behaviors.

Shu-Feng Tsao, Helen Hong Chen, Samantha B Meyer, Zahid A Butt

Abstract read
In one paragraph

Article in International journal of public health, 2024. 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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  5. Review
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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

4 authors.

Shu-Feng TsaoSchool of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada.
Helen Hong ChenSchool of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada.
Samantha B MeyerSchool of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada.
Zahid A ButtSchool of Public Health Sciences, Faculty of Health, University of Waterloo, Waterloo, ON, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Various communication and behavioral theories have been adopted to address health infodemics. However, there is no framework specially designed for social listening studies using social media data, machine learning, and natural language processing techniques. We aimed to propose a novel yet theory-based conceptual framework for infodemic research. We collected theories and models used in COVID-19 related studies published in peer-reviewed journals, ranging from health behavior, communication, to infodemic studies. These were analyzed and critiqued for their components, and we subsequently proposed a conceptual framework with a demonstration. Accordingly, we proposed our "Social Media Listening for Public Health Behavior" conceptual framework by not only integrating important attributes of existing theories, but also adding new attributes. The proposed conceptual framework can be used to better understand public discourse on social media, and can be integrated with other data analyses to gather a more comprehensive picture.

Indexed as

COVID-19Health BehaviorPublic HealthSocial MediaAlgorithmsAttitude to HealthHealth CommunicationHumansMachine LearningNatural Language Processingconceptual frameworkhealth infodemicmachine learningsocial listeningsocial media

Identifiers

PMID39611080
PMCPMC11602303

What OpenQuestion holds

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LicenceCC BY
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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.