Criminal network analysis and visualization
Communications of the ACM - 3d hard copy
Computational & Mathematical Organization Theory
Destabilization of covert networks
Computational & Mathematical Organization Theory
A framework for analysis of dynamic social networks
Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining
Identifying significant facilitators of dark network evolution
Journal of the American Society for Information Science and Technology
An event-based framework for characterizing the evolutionary behavior of interaction graphs
ACM Transactions on Knowledge Discovery from Data (TKDD)
A classification for community discovery methods in complex networks
Statistical Analysis and Data Mining
Applying Link Prediction to Ranking Candidates for High-Level Government Post
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
Group Evolution Discovery in Social Networks
ASONAM '11 Proceedings of the 2011 International Conference on Advances in Social Networks Analysis and Mining
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Among many real world applications of social network analysis, political interaction and executive succession show some unique characteristics of dynamic community evolution and raise interesting research challenges. Interactions of political power among community members are mostly subtle and behind the scene. Visible relations are only nominal and are not readily apparent to key findings. Under such difficult circumstances of information deficiency, the research problem is to uncover the inner relations among some of the network entities and to discover the hidden network structure based on these inner relations. In this research, our objective is to identify the inner circles of government political power and bureaucracy underneath formal work relations and observe how the political elite groups form and change over time. A government official job change network in a time span of over twenty years is built to model synchronous post assignment and job promotion within a time window as entity relations. In each snapshot of network evolution, communities that exhibit strong association of synchronous job change are identified by the edge betweenness decomposition algorithm. Then, an event-based framework is used to characterize community behavior patterns in consecutive changes of network structures. The approach is effectually demonstrated on two scenarios: (1) identifying and tracking the inner circle of a leading political figure, (2) finding succession pool members in government agencies. We further propose two evolutionary community variation indexes to assess political executive succession. Experimental results with actual government personnel data provide evidence that government agency succession can be reasonably measured. This work also has the practical value of providing objective scrutiny on political power transition for the benefit of public interest.