In this paper, we use activity traces to try to cluster users based on their behavior in an online genealogy wiki. We treat the wiki as a community of practice, and based on legitimate peripheral participation theories we expect that people will start in peripheral roles before moving to more central roles.
I presented some of my research from my master’s thesis about how people change between roles in the genealogy community WeRelate. I also spoke about some of the benefits of using a shared, open source family tree for genealogy collaboration.
Large peer production projects, such as Wikipedia and open source software, work surprisingly well in creating useful, large scale, and high quality artifacts. However, the vast majority of peer production projects fail to gain contributors or contributions. Because network scholars have focused on the rare successful projects, there is very little research on the factors that predict project growth in the first place. We approach this question by examining the network structures and participation dynamics of a diverse population of peer production communities as they are just starting.
I taught a lecture on digital exhaust and surveillance as part of the Computing Everywhere course run by Jeremy Birnholtz. I tried to combine a semi-technical explanation of how surveillance happens online with social theory (e.g., Lessig’s pathetic dot theory).
Both work groups and nascent peer production projects are composed of a small group of people, engaged in collaborative sense-making and knowledge production. The work group literature has found that dense, non-hierarchical interaction structures are associated with productive groups. Based on these findings, we hypothesize that these same structures would also lead to more productivity from new peer production communities. However, an analysis of 2,555 wiki communities shows that early interaction structures have very little impact on eventual productivity (as measured by total edits) or community growth (as measured by total contributors). Rather, a quickly growing group of active editors is a much better predictor of growth than the structure of interactions between them.
Abstract: Why do people start new online communities? Previous research has studied what helps communities to grow and what motivates contributors, but the reasons that people create new communities in the first place remain unclear. We present the results of a survey of over 300 founders of new communities on the online wiki hosting site Wikia.com. We analyze the motivations and goals of wiki creators, finding that founders have diverse reasons for starting wikis and diverse ways of defining their success. Many founders see their communities as occupying narrow topics, and neither seek nor expect a large group of contributors. We also find that founders with differing goals approach community building differently. We argue that community platform designers can create interfaces that support the diverse goals of founders more effectively.
Abstract: Online peer production projects, such as Wikipedia and open-source software, have become important producers of cultural and technological goods. While much research has been done on the way that large existing projects work, little is known about how projects get started or who starts them. Nor is it clear how much influence founders have on the future trajectory of a community. We measure the behavior and social networks of 60,959 users on Wikia.com over a two month period. We compare the activity, local network positions, and global network positions of future founders and non-founders. We then explore the relationship between these measures and the relative growth of a founder’s wikis. We suggest hypotheses for future research based on this exploratory analysis.
We were part of a great panel on agent-based modeling in communication research. Our work takes an interesting HCI-based model of community joining (Resnick et al., 2011) and tests what assumptions must be added in order for simulated agents to have similar outcomes as empirical communities.
I presented very similar work to the International Conference on Computational Social Science. I had some great conversations and feedback, and thought of some good new directions to take this research and publish it.