Dr. Sridhar Nerur, a Professor of Goolsby-Virginia and Paul Dorman Endowed Chair in Leadership at the University of Texas at Arlington will present a seminar on March 18 at 1:15pm in Nedderman Hall 105.
Title: Understanding Your Research Domain: Drawing Insights from Bibliometrics and Text Analysis
Author: Professor Sridhar Nerur
Location: Nedderman Hall Room 105
Date: Monday, March 18, 2019
Time: 1:15pm
Abstract: Scholars strive to extend the intellectual boundaries of their discipline by “standing on the shoulders of giants”. The first step in pursuing good research, therefore, is to have a good grasp of what has already been accomplished and what challenges remain. Regrettably, it takes an enormous amount of time and effort to sift through a discipline’s extensive corpora to understand the extant cumulative research traditions and the opportunities they afford for future research. Bibliometric tools that rely on citations and text mining algorithms that exploit the lexical structure of articles are increasingly being used to quickly unravel latent themes in large corpora. The purpose of this presentation is to demonstrate how such tools can accelerate the literature review process and provide insight that would otherwise take months of effort.
Biographical Sketch: Sridhar Nerur is currently Professor of Goolsby-Virginia and Paul Dorman Endowed Chair in Leadership at the University of Texas at Arlington. As Chair of the Graduate Studies Committee on Business Analytics, he has been actively involved in updating the curriculum to ensure that it is consistent with industry practices. His research has been published in the MIS Quarterly, Strategic Management Journal, Communications of the ACM, Communications of the AIS, The DATA BASE for Advances in Information Systems, European Journal of Information Systems, Information Systems Management, Information & Management, IEEE Software, and the Journal of International Business Studies. He has served as an associate editor of the European Journal of Information Systems, and was on the editorial board of the Journal of AIS until December 2016. His research and teaching interests include social networks, machine learning/AI, text analytics, self-organizing systems, and neuroeconomics.