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The detection of communities is a fundamental problem in the analysis of online networks. It allows to discover groups of closely connected actors in large networks and therefore to identify similarities or even areas of cooperation. Although ever more communication scientists study hyperlink networks to learn about the connections between civil society actors online, there is a lack of consensus on how to handle this task in a theoretically appropriate manner. We develop a typology of the social phenomena communities of hyperlinked actors are taken to signify – topical similarities, ideological associations, strategic alliances, and potential user traffic – and offer recommendations for community detection grounded in these concepts. Testing procedures on a real-world hyperlink network of the food safety movement, we show that the handling of tie directions and weights as well as the choice of algorithm have a major influence on the communities ultimately detected in such a network.
Daniela Stoltenberg, University of Münster
Daniel Maier, Free U of Berlin
Annie Waldherr, U of Muenster