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Essembly encourages its users to form online social relationships; the types of the links become central to how the user experiences the service. Traditional online social network sites use a single monolithic “friends” relationship to link users. In particular, Essembly prominently highlights the activities of users' acquaintances, and the question arises if this makes them more likely to participate, and if so, how this information affects votes. However, users  may even more in common with strangers, suggesting the use of a “similarity network” to recommend content. It is widely assumed that social networks enhance, if not drive, the popularity of online services; what does an additional layer of link classification add to them?


Essembly then allows its members to post resolves reflecting controversial opinions on political issues. Using both macroscopic and microscopic social dynamics, we present an analysis of Essembly, an ideological social network that semantically distinguishes between friends and ideological allies and nemeses. As a defining activity on the site, members can vote on these resolves on a four-point scale ranging from complete agreement to full opposition. Although users have greater similarity with their allies than their friends and nemeses, surprisingly, the allies network does not affect voting behavior, despite being as large as the friends network. In contrast, users are influenced differently by their friends and nemeses, indicating that people use these networks for distinct purposes.


We suggest resulting design implications for social content aggregation services and recommender systems.



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