Peer production communities have been proven to be successful at creating valuable artefacts, with Wikipedia as a prime example. However, a number of studies have shown that work in these communities tends to be of uneven quality and certain content areas receive more attention than others. In this paper, we examine the efficacy of a range of targeted strategies to increase the quality of under-attended content areas in peer production communities. Mining data from five quality improvement projects in the English Wikipedia, the largest peer production community in the world, we show that certain types of strategies (e.g. creating artefacts from scratch) have better quality outcomes than others (e.g. improving existing artefacts), even if both are done by a similar cohort of participants. We discuss the implications of our findings for Wikipedia as well as other peer production communities.

Session identification is a common strategy used to develop metrics for web analytics and behavioral analyses of userfacing systems. Past work has argued that session identification strategies based on an inactivity threshold is inherently arbitrary or 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 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.

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Wikipedia has become one of the primary encyclopaedic information repositories on the World Wide Web. It started in 2001 with a single edition in the English language and has since expanded to more than 20 million articles in 283 languages. Criss-crossing between the Wikipedias is an interlanguage link network, connecting the articles of one edition of Wikipedia to another. We describe characteristics of articles covered by nearly all Wikipedias and those covered by only a single language edition, we use the network to understand how we can judge the similarity between Wikipedias based on concept coverage, and we investigate the flow of translation between a selection of the larger Wikipedias. Our findings indicate that the relationships between Wikipedia editions follow Tobler's first law of geography: similarity decreases with increasing distance. The number of articles in a Wikipedia edition is found to be the strongest predictor of similarity, while language similarity also appears to have an influence. The English Wikipedia edition is by far the primary source of translations. We discuss the impact of these results for Wikipedia as well as user-generated content communities in general.

In peer production communities, individual community members typically decide for themselves where to make contributions, often driven by factors such as “fun” or a belief that “information should be free”. However, the extent to which this bottom-up, interest-driven content production paradigm meets the needs of consumers of this content is unclear. In this paper, we introduce an analytical framework for studying the relationship between content production and consumption in peer production communities. Applying our framework to four large Wikipedia language editions, we find extensive misalignment between production and consumption in all of them. We also show that this misalignment has an enormous effect on Wikipedias readers. For example, over 1.5 billion monthly pageviews in the English Wikipedia go to articles that would be of much higher quality if editors optimally distributed their work to meet reader demand. Examining misalignment in more detail, we observe that there is an excess of high-quality content about certain specific topics, and that the majority of articles with insufficient quality are in a stable state (i.e. not breaking news). Finally, we discuss technolo- gies and community practises that can help reduce the misalignment between the supply of and demand for high-quality content in peer production communities.