Title
Text Mining Using Latent Semantic Analysis: An Illustration Through Examination Of 30 Years Of Research A Jis
Abstract
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.
Year
DOI
Venue
2018
10.2308/isys-51625
JOURNAL OF INFORMATION SYSTEMS
Keywords
Field
DocType
text mining, latent semantic analysis, AIS research
Information system,Data science,World Wide Web,Text mining,Accounting information system,Computer science,Unstructured data,Latent semantic analysis,Big data
Journal
Volume
Issue
ISSN
32
1
0888-7985
Citations 
PageRank 
References 
1
0.36
19
Authors
3
Name
Order
Citations
PageRank
GUAN Jian14715.77
Alan Levitan2152.80
Sandeep Goyal311.38