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Online multiplayer games are a popular form of social interaction, used byhundreds of millions of individuals. However, little is known about the socialnetworks within these online games, or how they evolve over time. Understandinghuman social dynamics within massive online games can shed new light on socialinteractions in general and inform the development of more engaging systems.Here, we study a novel, large friendship network, inferred from nearly 18billion social interactions over 44 weeks between 17 million individuals in thepopular online game Halo: Reach. This network is one of the largest, mostdetailed temporal interaction networks studied to date, and provides a novelperspective on the dynamics of online friendship networks, as opposed to mereinteraction graphs. Initially, this network exhibits strong structural turnoverand decays rapidly from a peak size. In the following period, however, bothnetwork size and turnover stabilize, producing a dynamic structuralequilibrium. In contrast to other studies, we find that the Halo friendshipnetwork is non-densifying: both the mean degree and the average pairwisedistance are stable, suggesting that densification cannot occur whenmaintaining friendships is costly. Finally, players with greater long-termengagement exhibit stronger local clustering, suggesting a group-level socialengagement process. These results demonstrate the utility of online games forstudying social networks, shed new light on empirical temporal graph patterns,and clarify the claims of universality of network densification.

Social Network Dynamics in a Massive Online Game: Network Turnover, Non-densification, and Team Engagement in Halo Reach