Universität zu Köln

Indulska, Marta, Hovorka, Dirk S. and Recker, Jan C. ORCID: 0000-0002-2072-5792 (2012). Quantitative approaches to content analysis: Identifying conceptual drift across publication outlets. European journal of information systems : EJIS ; an official journal of the Operational Research Society, 21 (1). pp. 49-69. London: Taylor and Francis. ISSN 1476-9344

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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.

Item Type:	Journal Article
Creators:	Creators Email ORCID Indulska, Marta UNSPECIFIED UNSPECIFIED Hovorka, Dirk S. UNSPECIFIED UNSPECIFIED Recker, Jan C. UNSPECIFIED orcid.org/0000-0002-2072-5792
URN:	urn:nbn:de:hbz:38-87965
DOI:	10.1057/ejis.2011.37
Journal or Publication Title:	European journal of information systems : EJIS ; an official journal of the Operational Research Society
Publisher:	Taylor and Francis
ISSN:	1476-9344
Volume:	21
Number:	1
Subjects:	Data processing Computer science Management and auxiliary services
Uncontrolled Keywords:	Keywords Language unstructured data analysis English quantitative semantic analysis English text mining English Latent Semantic Analysis English
Faculty:	Faculty of Management, Economy and Social Sciences
Divisions:	Faculty of Management, Economy and Social Sciences > Cologne Institute for Information Systems (CIIS)
Language:	English
Date:	January 2012
Place of Publication:	London
Refereed:	Yes
Page Range:	pp. 49-69
URI:	http://kups.ub.uni-koeln.de/id/eprint/8796