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Longitudinal Dynamic Network Analysis Using the Over Time Viewer Feature in ORA

By Ian Mcculloh and Kathleen Carley


the Army Research Lab, the National Science Foundation, the Office of Naval Research or the U.S. government Keywords: networks, change detection, network evolution, longitudinal network analysis, dynamic network analysis. Analyzing network over time has become increasingly popular as longitudinal network data becomes more available. Longitudinal networks are studied by sociologists to understand network evolution, belief formation, friendship formation, diffusion of innovations, the spread of deviant behavior and more. Organizations are interested in studying longitudinal network in order to get inside the decision cycle of major events. Prior to important events occurring in an organization, there is likely to exist an earlier change in network dynamics. Being able to identify that a change in network dynamics has occurred can enable managers to respond to the change in network behavior prior to the event occurring and shape a favorable outcome. The Over Time Viewer is a software tool hosted by the CASOS software suite that enables the analysis of longitudinal dynamic network data. This report introduce

Year: 2009
OAI identifier: oai:CiteSeerX.psu:
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