Current theories struggle to explain how participants in peer-production self-organize to produce high-quality knowledge in the absence of formal coordination mechanisms. The literature traditionally holds that norms, policies, and roles make coordination possible. However, peer-production is largely free from workflow constraints and most peer-production communities do not allocate or assign tasks. Yet, scholars have suggested that ordered work sequences can emerge in such settings. We refer to sequences of activities that emerge organically as components of “emergent routines.” The volunteer nature of peer-production, coupled with high degrees of turnover, makes learning and coordination difficult, calling into question the extent to which emergent routines could be ingrained in the community. The objective of this article is to characterize the work sequences that organically emerge in peer-production, as well as to understand the temporal dynamics of these emergent routine components. We center our empirical investigation on the peer-production of a set of 1,000 Wikipedia articles. Using a dataset of labeled wiki work, we employ Variable-Length Markov Chains (VLMC) to identify sequences of activities exhibiting structural dependence, cluster the sequences to identify components of emergent routines, and then track their prevalence over time. We find that work is organized according to several routine components, and that the prevalence of these components changes over time.
|Number of pages||24|
|Journal||ACM Transactions on Social Computing|
|State||Published - 2020|