  We study the structural properties of large scale collaboration in online
communities of innovation and the role that position in the community plays in
determining knowledge contribution. Contrary to previous research, we argue for
a more local perspective when examining online collaboration. We demonstrate
that a member's centrality and spanning within his/her local neighborhood is a
better predictor of contribution than global centrality and spanning within the
whole community. We contribute both theoretically and methodologically to
research on large scale collaboration. On the theoretical front, a local view
of position implies a more confined and local organization of work in online
communities than previously thought. From a methodological perspective,
evaluating the local structure of large networks involves radically different
algorithms that have only recently become feasible with the increase of
processing power.
