Please use this identifier to cite or link to this item: http://hdl.handle.net/1942/40559
Title: The application of text mining in accounting
Authors: Senave, Elseline
JANS, Mieke 
Srivastava, Rajendra P.
Issue Date: 2023
Publisher: ELSEVIER
Source: International Journal of Accounting Information Systems, 50 (Art N° 100624)
Abstract: By facilitating the derivation of knowledge and qualitative measures from textual data, text mining techniques have come into vogue in various domains and industries. Namely in ac-counting, text mining outputs can elucidate, complement, and validate the customary quantita-tive data. This study creates an up-to-date view of text mining applications in accounting practice. Through a critical review of text mining literature, insight is given into the stages of a typical text mining process, contemporary text mining techniques that have been named valuable in an ac-counting context, and the information that can be obtained by applying these techniques.
Notes: Jans, MJ (corresponding author), Hasselt Univ, Martelarenlaan 42, B-3500 Hasselt, Belgium.; Jans, MJ (corresponding author), Maastricht Univ, Minderbroedersberg 4-6, NL-6211 LK Maastricht, Netherlands.
Keywords: Text mining;Accounting;Readability;Cosine similarity;Risk sentiment
Document URI: http://hdl.handle.net/1942/40559
ISSN: 1467-0895
e-ISSN: 1873-4723
DOI: 10.1016/j.accinf.2023.100624
ISI #: 001013457000001
Rights: 2023 Elsevier Inc. All rights reserved.
Category: A1
Type: Journal Contribution
Appears in Collections:Research publications

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