{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,1]],"date-time":"2026-04-01T19:33:08Z","timestamp":1775071988424,"version":"3.50.1"},"reference-count":45,"publisher":"American Accounting Association","issue":"1","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018,3,1]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n               <jats:p>Big Data presents a tremendous challenge for the accounting profession today. This challenge is characterized by, among other things, the explosive growth of unstructured data, such as text. In recent years, new text-mining methods have emerged to turn unstructured textual data into actionable information. A critical role of accounting information systems (AIS) research is to help the accounting profession assess and utilize these methodologies in an accounting context. This paper introduces the latent semantic analysis (LSA), a text-mining approach that discovers latent structures in unstructured textual data, to the AIS research community. An LSA-based approach is used to analyze AIS research as published in the Journal of Information Systems (JIS) over the last 30 years. JIS research serves as an appropriate domain of analysis because of a perceived need to contextualize the scope of AIS research. The research themes and trends resulting from this analysis contribute to a better understanding of this identity.<\/jats:p>","DOI":"10.2308\/isys-51625","type":"journal-article","created":{"date-parts":[[2016,10,17]],"date-time":"2016-10-17T21:06:19Z","timestamp":1476738379000},"page":"67-86","source":"Crossref","is-referenced-by-count":16,"title":["Text Mining Using Latent Semantic Analysis: An Illustration through Examination of 30 Years of Research at <i>JIS<\/i>"],"prefix":"10.2308","volume":"32","author":[{"given":"Jian","family":"Guan","sequence":"first","affiliation":[{"name":"University of Louisville"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alan S.","family":"Levitan","sequence":"additional","affiliation":[{"name":"University of Louisville"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sandeep","family":"Goyal","sequence":"additional","affiliation":[{"name":"University of Louisville"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1112","published-online":{"date-parts":[[2016,10,1]]},"reference":[{"key":"2024082915321243600_i1558-7959-32-1-67-Albright1","unstructured":"Albright, R. \n          \n          2004. 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B. \n          \n          2008. An Empirical Study of Required Dimensionality for Large-Scale Latent Semantic Indexing Applications. Proceedings of the 17th ACM Conference on Information and Knowledge Management, Napa Valley, CA, October 26\u201330.","DOI":"10.1145\/1458082.1458105"},{"issue":"2","key":"2024082915321243600_i1558-7959-32-1-67-BrownLiburd1","doi-asserted-by":"crossref","first-page":"451","DOI":"10.2308\/acch-51023","article-title":"Behavioral implications of Big Data's impact on audit judgment and decision making and future research directions","volume":"29","author":"Brown-Liburd","year":"2015","journal-title":"Accounting Horizons"},{"issue":"2","key":"2024082915321243600_i1558-7959-32-1-67-Chakraborty1","doi-asserted-by":"crossref","first-page":"122","DOI":"10.1016\/j.accinf.2014.01.001","article-title":"Automatic classification of accounting literature","volume":"15","author":"Chakraborty","year":"2014","journal-title":"International Journal of Accounting Information Systems"},{"key":"2024082915321243600_i1558-7959-32-1-67-Chakraborty2","unstructured":"Chakraborty, G., \n            \n              M. Pagolu, and S. Garla. \n          2014\n          b. Text Mining and Analysis: Practical Methods, Examples, and Case Studies Using SAS. 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K., \n            \n              D. S. McNamara, \n            \n              S. Dennis, and W. Kintsch. \n          2013. Handbook of Latent Semantic Analysis. Hove, U.K.: Psychology Press."},{"issue":"1","key":"2024082915321243600_i1558-7959-32-1-67-Larsen1","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1111\/j.0081-1750.2004.00156.x","article-title":"A mathematical approach to categorization and labeling of qualitative data: The latent categorization method","volume":"34","author":"Larsen","year":"2004","journal-title":"Sociological Methodology"},{"key":"2024082915321243600_i1558-7959-32-1-67-Manning1","doi-asserted-by":"crossref","unstructured":"Manning, C. D., \n            \n              P. Raghavan, and H. Sch\u00fctze. \n          2008. Introduction to Information Retrieval. Volume 1. 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Frank. \n          2005. Data Mining: Practical Machine Learning Tools and Techniques. 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