Emergent Routines in Peer-Production

Ofer Arazy, Aron Lindberg, Shakked Lev, Kexian Wu, Alex Yarovoy

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)1-24
Number of pages24
JournalACM Transactions on Social Computing
Volume3
Issue number1
DOIs
StatePublished - 2020

Fingerprint

Dive into the research topics of 'Emergent Routines in Peer-Production'. Together they form a unique fingerprint.

Cite this