Semantic Social Network Analysis for the Enterprise

Authors

  • Charalampos Chelmis Department of Computer Science, University of Southern California, 3740 McClintock Avenue, Los Angeles CA 90089-2562
  • Hao Wu Department of Computer Science, University of Southern California, 3740 McClintock Avenue, Los Angeles CA 90089-2562
  • Vikram Sorathia Ming Hsieh Dept. of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, Los Angeles CA 90089-2562
  • Viktor K. Prasanna Ming Hsieh Dept. of Electrical Engineering, University of Southern California, 3740 McClintock Avenue, Los Angeles CA 90089-2562

Abstract

Business processes are generally fixed and enforced strictly, as reflected by the static nature of underlying software systems and datasets. However, internal and external situations, organizational changes and various other factors trigger dynamism, which is reflected in the form of issues, complains, Q&A, opinions, reviews, etc, over a plethora of communication channels, such as email, chat, discussion forums, and internal social network. Careful and timely analysis and processing of such channels may lead to early detection of emerging trends, critical issues, opportunities, topics of interests, contributors, experts etc. Social network analytics have been successfully applied in general purpose, online social network platforms, like Facebook and Twitter. However, in order for such techniques to be useful in business context, it is mandatory to integrate them with underlying business systems, processes and practices. Such integration problem is increasingly recognized as Big Data problem. We argue that SemanticWeb technology applied with social network analytics can solve enterprise knowledge management, while achieving integration.

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Published

2015-02-04

How to Cite

Chelmis, C., Wu, H., Sorathia, V., & Prasanna, V. K. (2015). Semantic Social Network Analysis for the Enterprise. Computing and Informatics, 33(3), 479–502. Retrieved from http://147.213.75.17/ojs/index.php/cai/article/view/2214

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Section

Special Section Articles