Titlebook: Social Computing, Behavioral Modeling, and Prediction; Huan Liu,John J. Salerno,Michael J. Young Conference proceedings 2008 Springer-Verl

staging

An Ant Colony Optimization Approach to Expert Identification in Social Networks,lem. While the degree of separation between any node and an expert node may be small, assuming that social networks are small world networks, not all nodes may be willing to route the query because flooding the network with queries may result in the nodes becoming less likely to route queries in the

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空洞

Particle Swarm Social Model for Group Social Learning in Adaptive Environment,earning of self-organized groups and their collective searching behavior in an adaptive environment. The objective of this research is to apply the particle swarm metaphor as a model of social learning for a dynamic environment. The research provides a platform for understanding and insights into kn

Aggressive

Social Network Analysis: Tasks and Tools,. With many different ways to analyze social networks, no single tool currently supports all analysis tasks, but some incorporate more functionality than others. Moreover, the emergence of a new class of social network analysis techniques, link mining, presents a new range of analysis support to pro

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Community Detection in a Large Real-World Social Network,fficulty of the task.With a proliferation of real-world network datasets there has been an increasing demand for algorithms that work effectively and efficiently. Existing methods are limited by their computational requirements and rely heavily on the network topology, which fails in scale-free netw

卡死偷电

微生物

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Intentional

Mobile Phone Data for Inferring Social Network Structure,based on contextualized proximity and communication data alone, and identify characteristic behavioral signatures of relationships that allowed us to accurately predict 95% of the reciprocated friendships in the study. Using these behavioral signatures we can predict, in turn, individual-level outcomes such as job satisfaction.