Uncovering Organizational Hierarchies
Computational & Mathematical Organization Theory
Microscopic evolution of social networks
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Evolution of a location-based online social network: analysis and models
Proceedings of the 2012 ACM conference on Internet measurement conference
LaFT-tree: perceiving the expansion trace of one's circle of friends in online social networks
Proceedings of the sixth ACM international conference on Web search and data mining
Learning latent friendship propagation networks with interest awareness for link prediction
Proceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval
The role of information diffusion in the evolution of social networks
Proceedings of the 19th ACM SIGKDD international conference on Knowledge discovery and data mining
Simmelian backbones: amplifying hidden homophily in Facebook networks
Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
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Heider's balance theory is ubiquitous in the field of social networks as an explanation for why we so frequently observe symmetry and transitivity in social relations. We propose that Simmelian tie theory could explain the same phenomena without resorting to motivational tautologies that characterize psychological explanations. Further, while both theories predict the same equilibrium state, we argue that they suggest different processes by which this equilibrium is reached. We develop a dynamic exponential random graph model (ERGM) and apply it to the classic panel data collected by Newcomb to empirically explore these two theories. We find strong evidence that Simmelian triads exist and are stable beyond what would be expected through Heiderian tendencies in the data.