Title: Analysing organisational structures using social network analysis: a case study

Authors: C. Zhang, W.B. Hurst, R.B. Lenin, S. Ramaswamy

Addresses: Department of Applied Science, University of Arkansas at Little Rock, 2801 S. University Avenue, Little Rock, Arkansas 72204, USA. ' Department of Applied Science, University of Arkansas at Little Rock, 2801 S. University Avenue, Little Rock, Arkansas 72204, USA. ' Department of Mathematics, University of Central Arkansas, 201 Donaghey Avenue, Conway, Arkansas 72035, USA. ' Industrial Software Systems, ABB India, Corporate Research Center, Bangalore, India

Abstract: Fast communication technologies coupled with low-cost storage have aided enormous electronic data gathering. Hence, the need to transform such data to business intelligence and value is strong. In this paper, we focus on analysing e-mail corpuses (Enron) informational exchanges, with the intent to discern hidden organisational structure and cultures. We show that this provides deep insight about employee roles, and organisational structure that is of immense intrinsic value. We predict unknown employee statuses, and identify homogeneous groups and hierarchies amongst them. As a part of this work, we have developed a web-based Graphical User Interface (GUI) for feature extraction and composition.

Keywords: business intelligence; organisational hierarchies; classification; clustering; Enron; e-mail corpus; social network analysis; organisational structure; information exchange; organisational culture; employee roles; employee status.

DOI: 10.1504/IJIEM.2011.038390

International Journal of Internet and Enterprise Management, 2011 Vol.7 No.1, pp.104 - 127

Published online: 25 Apr 2015 *

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