텍스트 분석을 활용한 회계 연구의 현황과 전망

Abstract

[Purpose] The purpose of this study is to examine prior literature using text mining analysis techniques in the accounting area for identifying current research themes, to present other data analysis techniques, and to provide directions for future research and practice.
 [Methodology] For this study, I use the Systematic Literature Review(SLR) methodology adopted in Schmitz and Leoni(2019). The results are obtained by entering keywords of “text analysis’ and “accounting” in Google Scholar, and the prior researches reviewed in this paper are selected among them and their references, mainly with the papers published in major journals.
 [Findings] Sicne the 1990s overseas, and the 2000s in Korea, studies using text analysis in the accounting area have been started. However, there are not enough numbers of studies using the text mining analysis in the accounting, and the journals where these researches published are also limited. I find that most of the studies examine the relationship between quantitative information of financial statements and stock market responses using text analysis. It is also found that business/ audit/annual reports, sustainability reports, and disclosure data are used at the most. The data analysis techniques used in these studies are mostly opinion extraction, tone analysis, sentiment analysis, and frequency analysis, which investigates the amount of words or tone of data. In future business environments, non－financial and descriptive information such as sustainability reports, strategic reports and MD&A are expected to provide more useful information for decision－making, therefore, various types of data analysis techniques are needed to be more actively used in accounting research.
 [Implications] This paper contributes to review current research focus in text mining related accounting studies, identify research gaps, present future avenues of research, and introduce various types of data analysis techniques related to text mining. From a practical policy perspective, it is meaningful to suggest an improvement in the DART system and to drive efforts to establish XBRL, so that the text analysis studies can be more activated.