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Accession Number ADA564174
Title Evolve: Analyzing Evolving Social Networks.
Publication Date Jul 2012
Media Count 20p
Personal Author S. Macskassy
Abstract Many current social network analytic methods work by analyzing a static aggregate graph, which provides a limited view of the structure and behavior of real-world social networks. Social networks in reality are dynamic and evolve over time as people join or leave the networks and new connections form. This work investigates developing dynamic social network analysis (DSNA) methods to explicitly model time and heterogeneity. It focuses on two objectives: (1) Dynamic SNA metrics and methods which take time into account; (2) Predictive methods for modeling and predicting how individuals and groups change over time.
Keywords Communications networks
Dynamic network analysis
Learning machines
Social communication
Social network analysis
Time series analysis

Source Agency Non Paid ADAS
NTIS Subject Category 92C - Social Concerns
45C - Common Carrier & Satellite
Corporate Author University of Southern California, Marina del Rey. Information Sciences Inst.
Document Type Technical report
Title Note Final technical memo. Mar 2011-May 2012.
NTIS Issue Number 1302
Contract Number FA8750-11-C-0127

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