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How to detect and forecast corporate fraud by media reports? An approach using machine learning and qualitative comparative analysis

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成果类型:
期刊论文
作者:
Qiu, Shi;Luo, Yuansheng
通讯作者:
Luo, YS
作者机构:
[Qiu, Shi] Changsha Univ, Sch Econ & Management, Changsha, Peoples R China.
[Luo, Yuansheng] Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
通讯机构:
[Luo, YS ] C
Changsha Univ Sci & Technol, Sch Comp & Commun Engn, Changsha, Peoples R China.
语种:
英文
关键词:
corporate fraud;fraud triangle theory;logistical regression;media reports;QCA
期刊:
Journal of Forecasting
ISSN:
0277-6693
年:
2024
卷:
43
期:
1
页码:
58-80
基金类别:
This work is supported by the Hunan Provincial Nature Science Foundation under grant 2023JJ30088, the National Natural Science Foundation of China under grant 72174057, Scientific Research Project of the Education Department of Hunan Province under grant 21B0768, and the Project of the Achievement Evaluation Committee of Social Sciences in Hunan Province under grant XSP2023GLC056.
机构署名:
本校为通讯机构
院系归属:
计算机与通信工程学院
摘要:
The media plays an important role in detecting corporate financial fraud. However, little systematic research exists on the impact of media reports on corporate fraud detection; thus, our understanding of the impact is limited. Therefore, we are committed to determining how the configuration of different media report content systematically detects corporate fraud by logistical regression, grounded theory and qualitative comparative analysis (QCA). First, the media reports are classified into three major categories and 35 subclasses to determine their features through fraud triangle theory and ...

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