Characterizing and predicting activity in Semantic MediaWiki communities

Abstract. Semantic MediaWikis represent shared and discretionary da-tabases that allow a community of contributors to capture knowledge and to specify semantic features, such as properties for articles, relationships between articles, or concepts that filter articles for certain property val-ues. Today, Semantic MediaWikis have received a lot of attention by a range of different groups that aim to organize an array of different sub-jects and domain knowledge. However, while some Semantic MediaWiki projects have been thriving, others have failed to reach critical mass. We have collected and analyzed a total of 79 publicly available Semantic MediaWiki instances to learn more about these projects and how they differ from each other. Further, we conducted an empirical analysis using critical mass theory on Semantic MediaWiki communities to investigate whether activity or the number of registered users (or a mixture of both) are important for achieving critical mass. In addition, we conduct ex-periments aiming to predict user activity and the number of registered users at certain points in time. Our work provides new insights into Se-mantic MediaWiki communities, how they evolve and first insights into how they can be studied using critical mass theory.