Evidence map›Paper›PMID 36406006›Full record

ArticleScientometrics2023

Why are medical research articles tweeted? The news value perspective.

Tint Hla Hla Htoo, Na Jin-Cheon, Michael Thelwall

Abstract readNews
In one paragraph

Article in Scientometrics, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. 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.

Tint Hla Hla HtooWee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore.
Na Jin-CheonWee Kim Wee School of Communication and Information, Nanyang Technological University, Singapore, Singapore.
Michael ThelwallStatistical Cybermetrics Research Group, University of Wolverhampton, Wolverhampton, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Counts of tweets mentioning research articles are potentially useful as social impact altmetric indicators, especially for health-related topics. One way to help understand what tweet counts indicate is to find factors that associate with the number of tweets received by articles. Using news value theory, this study examined six characteristics of research papers that may cause some articles to be more tweeted than others. For this, we manually coded 300 medical journal articles about COVID-19. A statistical analysis showed that all six factors that make articles more newsworthy according to news value theory (importance, controversy, elite nations, elite persons, scale, news prominence) associated with higher tweet counts. Since these factors are hypothesised to be general human news selection criteria, the results give new evidence that tweet counts may be indicators of general interest to members of society rather than measures of societal impact. This study also provides a new understanding of the strong positive relationship between news mentions and tweet counts for articles. Instead of news coverage attracting tweets or the other way round (journalists noticing highly tweeted articles and writing about them), the results are consistent with newsworthy characteristics of articles attracting both tweets and news mentions.

Indexed as

AltmetricsCOVID-19News valueTwitter

Identifiers

PMID36406006
PMCPMC9660108

What OpenQuestion holds

Textmetadata
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.