Quantitative approaches to content analysis: identifying conceptual drift across publication outlets

Abstract

Unstructured text data, such as emails, blogs, contracts, academic publications, organizational documents, transcribed interviews, and even tweets, are important sources of data in Information Systems research. Various forms of qualitative analysis of the content of these data exist and have revealed important insights. Yet, to date, these analyses have been hampered by limitations of human coding of large data sets, and by bias due to human interpretation. In this paper, we compare and combine two quantitative analysis techniques to demonstrate the capabilities of computational analysis for content analysis of unstructured text. Specifically, we seek to demonstrate how two quantitative analytic methods, viz., Latent Semantic Analysis and data mining, can aid researchers in revealing core content topic areas in large (or small) data sets, and in visualizing how these concepts evolve, migrate, converge or diverge over time. We exemplify the complementary application of these techniques through an examination of a 25-year sample of abstracts from selected journals in Information Systems, Management, and Accounting disciplines. Through this work, we explore the capabilities of two computational techniques, and show how these techniques can be used to gather insights from a large corpus of unstructured text.

Keywords:

• unstructured data analysis
• quantitative semantic analysis
• text mining
• Latent Semantic Analysis

Additional information

Notes on contributors

Marta Indulska

About the authors

Marta Indulska is a senior lecturer at the UQ Business School, University of Queensland. Her main research interests are conceptual modelling, innovation, and compliance management. Indulska's work has been published in journals such as the MIS Quarterly, IEEE Transactions on Knowledge & Data Engineering, Information Systems, Journal of the Association for Information Systems, and she presented at numerous international conferences. She is on the editorial board of two international journals, a program committee member for numerous international conferences and workshops in the Information Systems and Information Technology area, and an organizing Chair for several academic events.

Dirk S Hovorka

Dirk S. Hovorka is an Associate Professor in Information Systems in the School of IT, Bond University, QLD, Australia. He holds degrees in Geology and Interdisciplinary Telecommunications, and received his Ph.D. in Information Systems from the University of Colorado. His research includes the philosophical foundations of IS research, the development of design theory, and the evolving role of information systems in science. In addition to presenting research at major international conferences, Hovorka has published research in the Journal of the Association for Information Systems (JAIS), Information Systems Journal, European Journal of Information Systems, Communication of the Association for Information Systems, Decision Support Systems, and has contributed numerous chapters to books. Hovorka serves on the editorial board for JAIS and is a program committee member for various conferences.

Jan Recker

Jan Recker is Alexander-von-Humboldt Fellow and Associate Professor for Information Systems at Queensland University of Technology in Brisbane, Australia. His main areas of research include methods and extensions for business process design and the usage of process design methods and tools in organizational practice. His work is published in the MIS Quarterly, Journal of the Association for Information Systems, Information Systems, European Journal of Information Systems, Information & Management, Scandinavian Journal of Information Systems and others. Recker is an Associate Editor for the Communications of the Association for Information Systems, a member of the editorial board of several international journals and serves on the program committee of various academic conferences.