An approach to identify influential building blocks and linkages in an information resource network

Authors:
Sudip Bhattacharjee;James R. Marsden;Harpreet Singh
Affiliations:
Department of Operations and Information Management, 2100 Hillside Road, U-1041, School of Business, University of Connecticut, Storrs, CT 06269-1041, United States;Department of Operations and Information Management, 2100 Hillside Road, U-1041, School of Business, University of Connecticut, Storrs, CT 06269-1041, United States and KU-Leuven, Leuven, Belgium;Information Systems and Operations Management (ISOM), 800 West Campbell Road, SM33, School of Management, University of Texas at Dallas, Richardson, TX 75080-3021, United States
Venue:
Decision Support Systems
Year:
2011

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Abstract

An information resource network (IRN) is a time-ordered and potentially interrelated set of information elements. Examples include papers within a research domain, blog postings dealing with a certain topic, and information records within a company. We present a structured analysis to identify influential building blocks and linkages in a general IRN and show that our approach can be used for large networks of information nodes. Our method compensates for biases that can emerge at the edges of such time-dependent networks. Importantly, our focus is on the information elements and not on the authors of such information. We illustrate this process using one example of a resource network - research papers in a given domain. Our method can be implemented in any domain that can be represented as time-ordered, interrelated components of information sets.