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Why are medical research articles tweeted? The news value perspective

Author

Listed:
  • Tint Hla Hla Htoo

    (Nanyang Technological University)

  • Na Jin-Cheon

    (Nanyang Technological University)

  • Michael Thelwall

    (University of Wolverhampton)

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.

Suggested Citation

  • Tint Hla Hla Htoo & Na Jin-Cheon & Michael Thelwall, 2023. "Why are medical research articles tweeted? The news value perspective," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 207-226, January.
  • Handle: RePEc:spr:scient:v:128:y:2023:i:1:d:10.1007_s11192-022-04578-1
    DOI: 10.1007/s11192-022-04578-1
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    References listed on IDEAS

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    1. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.
    2. Fereshteh Didegah & Timothy D. Bowman & Kim Holmberg, 2018. "On the differences between citations and altmetrics: An investigation of factors driving altmetrics versus citations for finnish articles," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(6), pages 832-843, June.
    3. Zohreh Zahedi & Rodrigo Costas & Paul Wouters, 2014. "How well developed are altmetrics? A cross-disciplinary analysis of the presence of ‘alternative metrics’ in scientific publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1491-1513, November.
    4. Mike Thelwall, 2018. "Early Mendeley readers correlate with later citation counts," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(3), pages 1231-1240, June.
    5. Ehsan Mohammadi & Mike Thelwall & Stefanie Haustein & Vincent Larivière, 2015. "Who reads research articles? An altmetrics analysis of Mendeley user categories," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(9), pages 1832-1846, September.
    Full references (including those not matched with items on IDEAS)

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