Mining the network value of customers
Proceedings of the seventh ACM SIGKDD international conference on Knowledge discovery and data mining
Mining knowledge-sharing sites for viral marketing
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Maximizing the spread of influence through a social network
Proceedings of the ninth ACM SIGKDD international conference on Knowledge discovery and data mining
Building Blocks, Cohort Genetic Algorithms, and Hyperplane-Defined Functions
Evolutionary Computation
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Relational learning via latent social dimensions
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Computer Science Review
Community Detection in Social Networks Using Information Diffusion
ASONAM '12 Proceedings of the 2012 International Conference on Advances in Social Networks Analysis and Mining (ASONAM 2012)
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Communities are vehicles for efficiently disseminating news, rumors, and opinions in human social networks. Modeling information diffusion through a network can enable us to reach a superior functional understanding of the effect of network structures such as communities on information propagation. The intrinsic assumption is that form follows function---rational actors exercise social choice mechanisms to join communities that best serve their information needs. Particle Swarm Optimization (PSO) was originally designed to simulate aggregate social behavior; our proposed diffusion model, PSODM (Particle Swarm Optimization Diffusion Model) models information flow in a network by creating particle swarms for local network neighborhoods that optimize a continuous version of Holland's hyperplane-defined objective functions. In this paper, we show how our approach differs from prior modeling work in the area and demonstrate that it outperforms existing model-based community detection methods on several social network datasets.