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COVID-19 and telemedicine: A netnography approach

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  • Arenas Gaitán, Jorge
  • Ramírez-Correa, Patricio E.

Abstract

The COVID-19 pandemic has consolidated some trends that already existed in our society. Perhaps one of the most visible is the transformation of society towards greater digitisation. Digitalisation has gained weight in all aspects of our lives, and from the point of view of the health system we find an example in the slow historical adoption of telemedicine, which contrasts sharply with the massive conversion to this technology as a tool for social distancing. In this sense, the homebound population is the one most affected by the pandemic and the one that could benefit the most from the use of telemedicine. Using a netnography approach and based on the stimulus-organism-response paradigm, this study proposes to analyse the evolution of perception about telemedicine using the opinions expressed on Twitter. The primary technical tasks of the study incorporate the analysis of topics and the review of emotions and positive image perception using natural language processing. Specifically, tweets about telemedicine generated by the Spanish community are analysed in this work. The findings show that the COVID-19 pandemic has affected emotions and topics of interest related to telemedicine. This has changed the image that it had and the behaviour of the Twitter community in Spain. In conclusion, the study results suggest that changes in health systems affect people's emotions and behaviours.

Suggested Citation

  • Arenas Gaitán, Jorge & Ramírez-Correa, Patricio E., 2023. "COVID-19 and telemedicine: A netnography approach," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
  • Handle: RePEc:eee:tefoso:v:190:y:2023:i:c:s0040162523001051
    DOI: 10.1016/j.techfore.2023.122420
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    as
    1. Hossain, Md Shamim & Rahman, Mst Farjana, 2022. "Detection of potential customers’ empathy behavior towards customers' reviews," Journal of Retailing and Consumer Services, Elsevier, vol. 65(C).
    2. Andrea Castro-Martinez & Paula Méndez-Domínguez & Aimiris Sosa Valcarcel & Joaquín Castillo de Mesa, 2021. "Social Connectivity, Sentiment and Participation on Twitter during COVID-19," IJERPH, MDPI, vol. 18(16), pages 1-19, August.
    3. Amankwah-Amoah, Joseph & Khan, Zaheer & Wood, Geoffrey & Knight, Gary, 2021. "COVID-19 and digitalization: The great acceleration," Journal of Business Research, Elsevier, vol. 136(C), pages 602-611.
    4. Grün, Bettina & Hornik, Kurt, 2011. "topicmodels: An R Package for Fitting Topic Models," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 40(i13).
    5. 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.
    6. Lei Zheng & Miao Miao & JiYoon Lim & Maorui Li & Shu Nie & Xiaojun Zhang, 2020. "Is Lockdown Bad for Social Anxiety in COVID-19 Regions?: A National Study in The SOR Perspective," IJERPH, MDPI, vol. 17(12), pages 1-12, June.
    7. Jan Recker, 2013. "Scientific Research in Information Systems," Progress in IS, Springer, edition 127, number 978-3-642-30048-6, June.
    8. Chensang Ye & Cong Cao & Jinjing Yang & Xiuyan Shao, 2022. "Explore How Online Healthcare Can Influence Willingness to Seek Offline Care," IJERPH, MDPI, vol. 19(13), pages 1-20, June.
    9. Kamboj, Shampy & Sarmah, Bijoylaxmi & Gupta, Shivam & Dwivedi, Yogesh, 2018. "Examining branding co-creation in brand communities on social media: Applying the paradigm of Stimulus-Organism-Response," International Journal of Information Management, Elsevier, vol. 39(C), pages 169-185.
    10. Kamal, Syeda Ayesha & Shafiq, Muhammad & Kakria, Priyanka, 2020. "Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM)," Technology in Society, Elsevier, vol. 60(C).
    11. Clement, Dr. Jessica & Crutzen, Prof. Nathalie, 2021. "How Local Policy Priorities Set the Smart City Agenda," Technological Forecasting and Social Change, Elsevier, vol. 171(C).
    12. Laato, Samuli & Islam, A.K.M. Najmul & Farooq, Ali & Dhir, Amandeep, 2020. "Unusual purchasing behavior during the early stages of the COVID-19 pandemic: The stimulus-organism-response approach," Journal of Retailing and Consumer Services, Elsevier, vol. 57(C).
    13. Feinerer, Ingo & Hornik, Kurt & Meyer, David, 2008. "Text Mining Infrastructure in R," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i05).
    14. Jesús Cambra-Fierro & Lily (Xuehui) Gao & Iguácel Melero-Polo & Lia Patrício, 2022. "Theories, constructs, and methodologies to study COVID-19 in the service industries," The Service Industries Journal, Taylor & Francis Journals, vol. 42(7-8), pages 551-582, June.
    15. Eroglu, Sevgin A. & Machleit, Karen A. & Davis, Lenita M., 2001. "Atmospheric qualities of online retailing: A conceptual model and implications," Journal of Business Research, Elsevier, vol. 54(2), pages 177-184, November.
    16. Rowe, Francisco & Mahony, Michael & Graells-Garrido, Eduardo & Rango, Marzia & Sievers, Niklas, 2021. "Using Twitter to Track Immigration Sentiment During Early Stages of the COVID-19 Pandemic," SocArXiv pc3za, Center for Open Science.
    17. Pandita, Shailesh & Mishra, Hari Govind & Chib, Shagun, 2021. "Psychological impact of covid-19 crises on students through the lens of Stimulus-Organism-Response (SOR) model," Children and Youth Services Review, Elsevier, vol. 120(C).
    18. Yuanyuan Cao & Junjun Li & Xinghong Qin & Baoliang Hu, 2020. "Examining the Effect of Overload on the MHealth Application Resistance Behavior of Elderly Users: An SOR Perspective," IJERPH, MDPI, vol. 17(18), pages 1-23, September.
    19. Heeyong Noh & Sungjoo Lee, 2019. "Where technology transfer research originated and where it is going: a quantitative analysis of literature published between 1980 and 2015," The Journal of Technology Transfer, Springer, vol. 44(3), pages 700-740, June.
    Full references (including those not matched with items on IDEAS)

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