Session identification is a common strategy used to develop metrics for web analytics and perform behavioral analyses of user-facing systems. Past work has argued that session identification strategies based on an inactivity threshold is inherently arbitrary or has advocated that thresholds be set at about 30 minutes. In this work, we demonstrate a strong regularity in the temporal rhythms of user initiated events across several different domains of online activity (incl. video gaming, search, page views and volunteer contributions). We describe a methodology for identifying clusters of user activity and argue that the regularity with which these activity clusters appear implies a good rule-of-thumb inactivity threshold of about 1 hour. We conclude with implications that these temporal rhythms may have for system design based on our observations and theories of goal-directed human activity.

Open collaboration communities thrive when participation is plentiful. Recent research has shown that the English Wikipedia community has constructed a vast and accurate information resource primarily through the monumental effort of a relatively small number of active, volunteer editors. Beyond Wikipedia's active editor community is a substantially larger pool of potential participants: readers. In this paper we describe a set of field experiments using the Article Feedback Tool, a system designed to elicit lightweight contributions from Wikipedia's readers. Through the lens of social learning theory and comparisons to related work in open bug tracking software, we evaluate the costs and benefits of the expanded participation model and show both qualitatively and quantitatively that peripheral contributors add value to an open collaboration community as long as the cost of identifying low quality contributions remains low.