Big Data Analytics Using Network Science

This presentation describes the use of network science for analyzing data with high dimensionality and the need to introduce network science in classrooms. This study created a generalized method where inputs to the deep learning models are inferred through network methodology. Subsequently, the applications of network science in industry are discussed and a use case demonstrated using Gephi, an open-source tool, in which a network of diseases was created. This demonstration can be easily adopted for classrooms.

Authors:  Pankush Kalgotra, Auburn University and Ramesh Sharda, Oklahoma State University

About the Authors

Dr. Pankush Kalgotra is an Assistant Professor, Department of Systems and Technology at Auburn University. He earned his PhD in Management Science and Information Systems from Oklahoma State University. He has an MS in Management Information Systems from Oklahoma State University and a BTech in Information Technology from National Institute of Technology Raipur in India.

Dr. Kalgotra’s research interests include healthcare analytics, network science, neuroimaging in information systems and the dark side of information technology. His recent articles have appeared in journals such as Journal of Management Information Systems, European Journal of Information Systems, Journal of Business Research, Nature’s Scientific Reports, International Journal of Medical Informatics, International Journal of Hospitality Management, Information Systems Frontiers, Expert Systems with Applications, Communications of the Association for Information Systems, International Journal of Information Management, Computer Methods and Programs in Biomedicine, Decision Sciences Journal of Innovative Education and others.

Dr. Ramesh Sharda is the Vice Dean for Research and the Watson Graduate School of Management, Watson/ConocoPhillips Chair and a Regents Professor of Management Science and Information Systems in the Spears School of Business at Oklahoma State University. He has coauthored two textbooks (Analytics, Data Science, and Artificial Intelligence: Systems for Decision Support, 11th edition, Pearson and Business Intelligence, Analytics, and Data Science: A Managerial Perspective, 4th Edition, Pearson). His research has been published in major journals in management science and information systems including Management Science, Operations Research, Information Systems Research, Decision Support Systems, Interfaces, INFORMS Journal on Computing, and many others. He is a member of the editorial boards of journals such as the Decision Support Systems, Decision Sciences, ACM Database, and Information Systems Frontiers. He served as the Executive Director of Teradata University Network through 2020 and was inducted into the Oklahoma Higher Education Hall of Fame in 2016. Ramesh is a Fellow of INFORMS and AIS.