How to channel knowledge coproduction behavior in an online community: Combining machine learning and narrative analysis

Jialing Liu, Jiang Wei, Yang Liu and Duo Jin

Technological Forecasting and Social Change, 2022, vol. 183, issue C

Abstract: With ambiguous role definitions and without traditional organizational control or coordination mechanisms, how could online community channel knowledge coproduction behaviors among participants with heterogeneity roles? By using a novel theory-building method combining machine learning and narrative analysis, we investigate the heterogeneity of participant roles and knowledge coproduction channeling behaviors in a Chinese self-organizing online community—Miui.com, launched by Xiaomi Inc. Using latent Dirichlet allocation topic modeling analysis and a complementary qualitative analysis of community participants' online forum posts, we initially identify three types of participant role in the community: leaders, supporters, and integrators, and find that (a) conceptualizing narrative practice is adopted to promote knowledge collaboration for leaders; (b) serializing and anthologizing narrative practices are used to promote knowledge collaboration for supporters; and (c) anthologizing narrative practice is adopted to promote knowledge collaboration for integrators. Our study advances the theoretical understanding of the knowledge coproduction and value creation in online communities.

Keywords: Online community; Participant role; Narrative practice; Knowledge coproduction (search for similar items in EconPapers)
Date: 2022
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Persistent link: https://EconPapers.repec.org/RePEc:eee:tefoso:v:183:y:2022:i:c:s0040162522004103

DOI: 10.1016/j.techfore.2022.121887

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