It is rotating leaders who build the swarm: social network determinants of growth for healthcare virtual communities of practice
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Abstract (arXiv)
Purpose: The purpose of this paper is to identify the factors influencing the growth of healthcare virtual communities of practice (VCoPs) through a seven-year longitudinal study conducted using metrics from social-network and semantic analysis. By studying online communication along the three dimensions of social interactions (connectivity, interactivity and language use), the authors aim to provide VCoP managers with valuable insights to improve the success of their communities. Design/methodology/approach: Communications over a period of seven years (April 2008 to April 2015) and between 14,000 members of 16 different healthcare VCoPs coexisting on the same web platform were analysed. Multilevel regression models were used to reveal the main determinants of community growth over time. Independent variables were derived from social network and semantic analysis measures. Findings: Results show that structural and content-based variables predict the growth of the community. Progressively, more people will join a community if its structure is more centralised, leaders are more dynamic (they rotate more) and the language used in the posts is less complex. Research limitations/implications: The available data set included one Web platform and a limited number of control variables. To consolidate the findings of the present study, the experiment should be replicated on other healthcare VCoPs. Originality/value: The study provides useful recommendations for setting up and nurturing the growth of professional communities, considering, at the same time, the interaction patterns among the community members, the dynamic evolution of these interactions and the use of language. New analytical tools are presented, together with the use of innovative interaction metrics, that can significantly influence community growth, such as rotating leadership.
Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Builds on 1 of its 125 references that are in the map. First posted on arXiv 26 May 2021.
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1 of 125 references.
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Citing papers per year: 2021: 3.
3 papers.
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- 2021From words to connections: Word use similarity as an honest signal conducive to employees' digital communication11 Nov 2021
- 2021Put your money where your mouth is: Using deep learning to identify consumer tribes from word usage27 May 2021
- 2021Finding top performers through email patterns analysis27 May 2021