潜在语义分析在会计研究中的应用

IF 0.4 Q4 COMPUTER SCIENCE, INFORMATION SYSTEMS
P. Hutchison, Benjamin T. George, Binod Guragai
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引用次数: 0

摘要

本研究的目的是回顾一种文本主题建模方法,即潜在语义分析(LSA),并为研究人员提供必要的知识,使他们能够使用LSA学习和实施自己的会计研究。作者首先提供了一个简短的文献综述先前的商业和会计研究研究,已利用LSA的方法。使用提供的数据集,作者通过复制Hutchison, Plummer和George (2018b)进行的LSA研究中使用的力学,介绍了如何在研究中使用LSA的详细信息。他们的目的是在数据选择、分析平台和进行LSA研究所需的必要步骤方面提供全面的指导。本文还简要地比较了LSA与其他主题建模方法,提出了几种可以利用LSA的会计研究机会,并概述了LSA的局限性。数据可用性:数据可从文本中引用的公共来源获得;样本数据集可下载,见脚注5。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Application of Latent Semantic Analysis in Accounting Research
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.
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来源期刊
African Journal of Information Systems
African Journal of Information Systems COMPUTER SCIENCE, INFORMATION SYSTEMS-
自引率
14.30%
发文量
0
审稿时长
30 weeks
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