Latent Groups in Online Communities: a Longitudinal Study in Wikipedia
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Research on online communities has shown that content production involves manifest groups and latent users. This paper conceptualizes a related but distinct phenomenon of latent groups. We ground this contribution in a longitudinal study on the Finnish Wikipedia (2007–2014). In the case of experts working on content within their area of expertise, individuals can constitute a group that maintains itself over time. In such a setting, it becomes viable to view the group as an acting unit instead of as individual nodes in a network. Such groups are able to sustain their activities even over periods of inactivity. Our theoretical contribution is the conceptualization of latent groups, which includes two conditions: 1) a group is capable of reforming after inactivity (i.e., dormant ), and 2) a group is difficult to observe to an outsider (i.e., non-manifest ).
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Number of citations to item: 5
- Yael Sidi, Ina Blau, Tamar Shamir‐Inbal (2022): Mapping active and collaborative learning in higher education through annotations in <scp>hyper‐video</scp> by learning analytics, In: Journal of Computer Assisted Learning 6(38), doi:10.1111/jcal.12714
- Arto Lanamäki, Juho Lindman (2017): Before the Sense of 'We', In: Proceedings of the 13th International Symposium on Open Collaboration, doi:10.1145/3125433.3125451
- Ina Blau, Tamar Shamir-Inbal (2021): Writing private and shared annotations and lurking in Annoto hyper-video in academia: Insights from learning analytics, content analysis, and interviews with lecturers and students, In: Educational Technology Research and Development 2(69), doi:10.1007/s11423-021-09984-5
- Christophe Emmanuel Premat (2020): Wikipedia Practices, Quick Facts, and Plagiarism in Higher Education, In: Advances in Higher Education and Professional Development, doi:10.4018/978-1-7998-2265-3.ch009
- Houcemeddine Turki, Dariusz Jemielniak, Mohamed A. Hadj Taieb, Jose E. Labra Gayo, Mohamed Ben Aouicha, Mus’ab Banat, Thomas Shafee, Eric Prud’hommeaux, Tiago Lubiana, Diptanshu Das, Daniel Mietchen (2022): Using logical constraints to validate statistical information about disease outbreaks in collaborative knowledge graphs: the case of COVID-19 epidemiology in Wikidata, In: PeerJ Computer Science, doi:10.7717/peerj-cs.1085