Using Text Mining Technique for Auditors’ Reports

• Main Authors: Chang, Chun-wei, 張竣維
• Other Authors: Hung, Yu-Chun
• Format: Others
• Language: zh-TW
• Published: 2018
• Online Access: http://ndltd.ncl.edu.tw/handle/mgajfa

碩士 === 國立中正大學 === 會計與資訊科技研究所 === 106 === In the era of highly information technology development, the speed of information dissemination becomes faster than ever. In the field of uncovering financial reports, releasing financial reports by using open data becomes faster than by traditional ways. Therefore, researchers can analyze financial reports in a faster way. In the past decades, many accounting auditing researchers focus on quantitative data of financial report. However, this research conducts analyses by qualitative data of financial report. This study utilizes XBRL provided by Market Observation Post System to extract financial reports, extracts key words to establish thesaurus, and finally analyze qualitative data by R language. It is expect to provide understanding of financial reports from different perspectives. This study utilize Auditing Standards Bulletin to extrtact key words and to establish tresaurus. Then, Jieba algorithm is applied to do frequency analysis of key words. The research findings reveal that the concern about Sustainable development of firms will result in Modified unqualified opinion. Of firms with the concern about Sustainable development, huge loss is the most frequent words occurred.