Application of Latent Semantic Analysis in Accounting Research

被引:1
|
作者
Hutchison, Paul D. [1 ]
George, Benjamin [2 ]
Guragai, Binod [3 ]
机构
[1] Univ North Texas, Dept Accounting, Denton, TX 76205 USA
[2] Univ Toledo, Dept Informat Operat & Technol Management, Toledo, OH USA
[3] Texas State Univ, Dept Accounting, San Marcos, TX USA
关键词
text mining; latent semantic analysis; LSA; natural language processing; TEXTUAL ANALYSIS; DISCLOSURES; EARNINGS; JOURNALS;
D O I
10.2308/ISYS-2022-013
中图分类号
F8 [财政、金融];
学科分类号
0202 ;
摘要
The purpose of this study is to review a text topic modeling methodology, latent semantic analysis (LSA), and provide researchers with the requisite knowledge to allow them to learn and implement their own accounting research study using LSA. The authors first provide a brief literature review of prior business and accounting research studies that have utilized the LSA methodology. Using a provided dataset, the authors present details of how to employ LSA in a research study by replicating the mechanics used in an LSA study conducted by Hutchison, Plummer, and George (2018b). Their intent is to present thorough guidance on data selection, the analysis platform, and the necessary steps needed to conduct LSA research. This article also briefly compares LSA with other topic modeling methodologies, presents several accounting research opportunities where LSA could be utilized, and outlines LSA's limitations.Data Availability: Data are available from the public sources cited in the text; sample dataset is available for download, see footnote 5.
引用
收藏
页码:139 / 155
页数:17
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