An understanding of participation dynamics within online production communities requires an examination of the roles assumed by participants. Recent studies have established that the organizational structure of such communities is not flat; rather, participants can take on a variety of well-defined functional roles. What is the nature of functional roles? How have they evolved? And how do participants assume these functions? Prior studies focused primarily on participants' activities, rather than functional roles. Further, extant conceptualizations of role transitions in production communities, such as the Reader to Leader framework, emphasize a single dimension: organizational power, overlooking distinctions between functions. In contrast, in this paper we empirically study the nature and structure of functional roles within Wikipedia, seeking to validate existing theoretical frameworks. The analysis sheds new light on the nature of functional roles, revealing the intricate "career paths" resulting from participants' role transitions.
Many activities of editors in Wikipedia can be traced using its database dumps, which register detailed information about every single change to every article. Several researchers have used this information to gain knowledge about the production process of articles, and about activity patterns of authors. In this analysis, we have focused on one of those previous works, by Kittur et al. First, we have followed the same methodology with more recent and comprehensive data. Then, we have extended this methodology to precisely identify which fraction of authors are producing most of the changes in Wikipedia's articles, and how the behaviour of these authors evolves over time. This enabled us not only to validate some of the previous results, but also to find new interesting evidences. We have found that the analysis of sysops is not a good method for estimating different levels of contributions, since it is dependent on the policy for electing them (which changes over time and for each language). Moreover, we have found new activity patterns classifying authors by their contributions during specific periods of time, instead of using their total number of contributions over the whole life of Wikipedia. Finally, we present a tool that automates this extended methodology, implementing a quick and complete quantitative analysis of every language edition in Wikipedia.
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