This brief presents readers with a summary of classic, modern, and state-of-the-art methods for discovering the roles of entities in networks (including social networks) that range from small to large-scale. It classifies methods by their mathematical underpinning, whether they are driven by implications about entity behaviors in system, or if they are purely data driven. The brief also discusses when and how each method should be applied, and discusses some outstanding challenges toward the development of future role mining methods of each type.

Includes supplementary material: sn.pub/extras

Autorentext
Derek Doran is an Assistant Professor in the Department of Computer Science and Engineering at Wright State University in Dayton, OH. His research interests are in analyzing, modeling, and making sense of data generated from complex systems by their relational structure, with an emphasis on web, social, and geospatial systems. His publications on large-scale network analysis, social media mining, and data science pedagogy have been recognized with best paper awards and nominations, and is an inventor on multiple patents on network analysis. Dr. Doran is a National Science Foundation EAPSI Fellow, a Graduate Research Awardee of the Transportation Research Board of the National Academies, a twice summer alumnus of Bell Labs, and before joining Wright State University, was an interim researcher in the (Big) Data Analytics team at ABB Corporate Research.

Inhalt
Network Role Mining and Analysis: An Overview.- Implied Role Mining.- Equivalence-Based Role Mining.- Deterministic Blockmodeling.- Stochastic Blockmodeling.- Advanced Computational Methods.- Concluding Remarks.