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eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis

Author

Listed:
  • Caroll Hermann

    (Department of Psychology, University of Zululand, KwaDlangezwa Campus, Richards Bay 3886, South Africa)

  • Melanie Govender

    (Department of Psychology, University of Zululand, KwaDlangezwa Campus, Richards Bay 3886, South Africa)

Abstract

Understanding social media networks and group interactions is crucial to the advancement of linguistic and cultural behavior. This includes how people accessed advice on health during COVID-19 lockdown. Some people turned to social media to access information on health when other routes were curtailed by isolation rules, particularly among older generations. Facebook public pages, groups and verified profiles using keywords “senior citizen health”, “older generations”, and “healthy living” were analyzed over a 12-month period to examine engagement with social media promoting good mental health. CrowdTangle was used to source status updates, photo and video sharing information in the English language, which resulted in an initial 116,321 posts and 6,462,065 interactions. Data analysis and visualization were used to explore large datasets, including natural language processing for “message” content discovery, word frequency and correlational analysis as well as co-word clustering. Preliminary results indicate strong links to healthy aging information shared on social media, which showed correlations to global daily confirmed cases and daily deaths. The results can identify public concerns early on and address mental health issues among senior citizens on Facebook.

Suggested Citation

  • Caroll Hermann & Melanie Govender, 2022. "eHealth Engagement on Facebook during COVID-19: Simplistic Computational Data Analysis," IJERPH, MDPI, vol. 19(8), pages 1-15, April.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:8:p:4615-:d:791684
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    References listed on IDEAS

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    1. Delmastro, Marco & Zollo, Fabiana, 2021. "Viewpoint: Social monitoring for food policy and research: Directions and implications," Food Policy, Elsevier, vol. 105(C).
    2. Firdos Khan & Shaukat Ali & Alia Saeed & Ramesh Kumar & Abdul Wali Khan, 2021. "Forecasting daily new infections, deaths and recovery cases due to COVID-19 in Pakistan by using Bayesian Dynamic Linear Models," PLOS ONE, Public Library of Science, vol. 16(6), pages 1-14, June.
    3. Chiara Fossati & Guglielmo Torre & Sebastiano Vasta & Arrigo Giombini & Federico Quaranta & Rocco Papalia & Fabio Pigozzi, 2021. "Physical Exercise and Mental Health: The Routes of a Reciprocal Relation," IJERPH, MDPI, vol. 18(23), pages 1-10, November.
    4. Manon Berriche & Sacha Altay, 2020. "Internet users engage more with phatic posts than with health misinformation on Facebook," Palgrave Communications, Palgrave Macmillan, vol. 6(1), pages 1-9, December.
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    Cited by:

    1. Arenas Gaitán, Jorge & Ramírez-Correa, Patricio E., 2023. "COVID-19 and telemedicine: A netnography approach," Technological Forecasting and Social Change, Elsevier, vol. 190(C).

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