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Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice

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  • Weiai Xu
  • I-Hsuan Chiu
  • Yixin Chen
  • Tanuka Mukherjee

Abstract

We utilize network and content analyses to examine the health-related conversations via Twitter hashtags. The study is an extension of the Leveraging Internet for Knowledge Sharing model to the new Twitter context. The findings show that the conversations involve the themes of knowledge sharing, nurturing relationship (community), and activism/advocacy/promotion (action). The conversation networks are decentralized, with advocates, healthcare providers, and average individuals being the central participants. Conversations flow most frequently between participants of the same healthcare roles, yet there is a considerable amount of conversations from healthcare providers to average consumers, and from average consumers to media. It is also noted that most conversations are not continuous or reciprocal. The findings and their implications are discussed in relation to the characteristics of communities of practice. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Weiai Xu & I-Hsuan Chiu & Yixin Chen & Tanuka Mukherjee, 2015. "Twitter hashtags for health: applying network and content analyses to understand the health knowledge sharing in a Twitter-based community of practice," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(4), pages 1361-1380, July.
    • Handle: RePEc:spr:qualqt:v:49:y:2015:i:4:p:1361-1380
    DOI: 10.1007/s11135-014-0051-6
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    Cited by:

    1. Katharina Baum & Annika Baumann & Katharina Batzel, 2024. "Investigating Innovation Diffusion in Gender-Specific Medicine: Insights from Social Network Analysis," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 66(3), pages 335-355, June.
    2. Hong, Yoo Jung & Shin, Donghee & Kim, Jang Hyun, 2016. "High/low reputation companies' dialogic communication activities and semantic networks on Facebook: A comparative study," Technological Forecasting and Social Change, Elsevier, vol. 110(C), pages 78-92.
    3. Rocco Agrifoglio & Paola Briganti & Concetta Metallo & Luisa Varriale, 2023. "Virtual healthcare communities of practice: An Italian experience during the Covid-19 pandemic," MECOSAN, FrancoAngeli Editore, vol. 2023(125), pages 11-28.
    4. Peng Wang & Fang-Wei Zhu & Hao-Yang Song & Jian-Hua Hou & Jin-Lan Zhang, 2018. "Visualizing the Academic Discipline of Knowledge Management," Sustainability, MDPI, vol. 10(3), pages 1-28, March.
    5. Elena Milani & Emma Weitkamp & Peter Webb, 2020. "The Visual Vaccine Debate on Twitter: A Social Network Analysis," Media and Communication, Cogitatio Press, vol. 8(2), pages 364-375.
    6. Devendra Potnis & Iman Tahamtan, 2021. "Hashtags for gatekeeping of information on social media," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(10), pages 1234-1246, October.
    7. Salvatore Pirri & Valentina Lorenzoni & Gianni Andreozzi & Marta Mosca & Giuseppe Turchetti, 2020. "Topic Modeling and User Network Analysis on Twitter during World Lupus Awareness Day," IJERPH, MDPI, vol. 17(15), pages 1-18, July.

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