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What Are You Saying? Using topic to Detect Financial Misreporting

Citations

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Cited by:

  1. Zhan, Baoqiang & Wu, Chong, 2024. "Star power: A quasi-natural experiment on how analyst status affects recommendation performance," Finance Research Letters, Elsevier, vol. 59(C).
  2. Li, Guowen & Wang, Shuai & Feng, Yuyao, 2024. "Making differences work: Financial fraud detection based on multi-subject perceptions," Emerging Markets Review, Elsevier, vol. 60(C).
  3. Anastassia Fedyk & James Hodson & Natalya Khimich & Tatiana Fedyk, 2022. "Is artificial intelligence improving the audit process?," Review of Accounting Studies, Springer, vol. 27(3), pages 938-985, September.
  4. Ge Zhang & Yuxiang Gao & Gaoyong Li, 2023. "Research on Digital Transformation and Green Technology Innovation—Evidence from China’s Listed Manufacturing Enterprises," Sustainability, MDPI, vol. 15(8), pages 1-23, April.
  5. Achakzai, Muhammad Atif Khan & Peng, Juan, 2023. "Detecting financial statement fraud using dynamic ensemble machine learning," International Review of Financial Analysis, Elsevier, vol. 89(C).
  6. Charles P. Cullinan & Richard Holowczak & David Louton & Hakan Saraoglu, 2023. "Costs associated with exit or disposal activities: A topic modeling investigation of disclosure and market reaction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 30(4), pages 173-191, October.
  7. Ruijie Sun & Feng Liu & Yinan Li & Rongping Wang & Jing Luo, 2024. "Machine Learning for Predicting Corporate Violations: How Do CEO Characteristics Matter?," Journal of Business Ethics, Springer, vol. 195(1), pages 151-166, November.
  8. Shuili Du & Assaad El Akremi & Ming Jia, 2023. "Quantitative Research on Corporate Social Responsibility: A Quest for Relevance and Rigor in a Quickly Evolving, Turbulent World," Journal of Business Ethics, Springer, vol. 187(1), pages 1-15, September.
  9. Zhao, Shuping & Xu, Kai & Wang, Zhao & Liang, Changyong & Lu, Wenxing & Chen, Bo, 2022. "Financial distress prediction by combining sentiment tone features," Economic Modelling, Elsevier, vol. 106(C).
  10. Chen, Cathy Yi-Hsuan & Fengler, Matthias R. & Härdle, Wolfgang Karl & Liu, Yanchu, 2022. "Media-expressed tone, option characteristics, and stock return predictability," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
  11. Bhattacharya, Indranil & Mickovic, Ana, 2024. "Accounting fraud detection using contextual language learning," International Journal of Accounting Information Systems, Elsevier, vol. 53(C).
  12. Blankespoor, Elizabeth, 2022. "Understanding investor interaction with firm information: A discussion of Lee and Zhong (2022)," Journal of Accounting and Economics, Elsevier, vol. 74(2).
  13. Fengler, Matthias & Phan, Minh Tri, 2023. "A Topic Model for 10-K Management Disclosures," Economics Working Paper Series 2307, University of St. Gallen, School of Economics and Political Science.
  14. Tang, Wenjin & Bu, Hui & Zuo, Yuan & Wu, Junjie, 2024. "Unlocking the power of the topic content in news headlines: BERTopic for predicting Chinese corporate bond defaults," Finance Research Letters, Elsevier, vol. 62(PA).
  15. Zhao, Qi & Xu, Weijun & Ji, Yucheng, 2023. "Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?," International Review of Financial Analysis, Elsevier, vol. 89(C).
  16. So-Jin Yu & Jin-Sung Rha, 2021. "Research Trends in Accounting Fraud Using Network Analysis," Sustainability, MDPI, vol. 13(10), pages 1-26, May.
  17. Belen Blanco & Sandip Dhole & Ferdinand A. Gul, 2023. "Financial statement comparability and accounting fraud," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 50(7-8), pages 1166-1205, July.
  18. Xin Xu & Feng Xiong & Zhe An, 2023. "Using Machine Learning to Predict Corporate Fraud: Evidence Based on the GONE Framework," Journal of Business Ethics, Springer, vol. 186(1), pages 137-158, August.
  19. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  20. Rong Liu & Jujun Huang & Zhongju Zhang, 2023. "Tracking disclosure change trajectories for financial fraud detection," Production and Operations Management, Production and Operations Management Society, vol. 32(2), pages 584-602, February.
  21. Essi Nousiainen & Mikko Ranta & Mika Ylinen & Marko Järvenpää, 2024. "Using machine learning and 10‐K filings to measure innovation," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(4), pages 3211-3239, December.
  22. Düsterhöft, Maximilian & Schiemann, Frank & Walther, Thomas, 2023. "Let’s talk about risk! Stock market effects of risk disclosure for European energy utilities," Energy Economics, Elsevier, vol. 125(C).
  23. Yunchuan Sun & Xiaoping Zeng & Ying Xu & Hong Yue & Xipu Yu, 2024. "An intelligent detecting model for financial frauds in Chinese A‐share market," Economics and Politics, Wiley Blackwell, vol. 36(2), pages 1110-1136, July.
  24. Lukui Huang & Alan Abrahams & Peter Ractham, 2022. "Enhanced financial fraud detection using cost‐sensitive cascade forest with missing value imputation," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(3), pages 133-155, July.
  25. Evangelos Liaras & Michail Nerantzidis & Antonios Alexandridis, 2024. "Machine learning in accounting and finance research: a literature review," Review of Quantitative Finance and Accounting, Springer, vol. 63(4), pages 1431-1471, November.
  26. Richard Frankel & Jared Jennings & Joshua Lee, 2022. "Disclosure Sentiment: Machine Learning vs. Dictionary Methods," Management Science, INFORMS, vol. 68(7), pages 5514-5532, July.
  27. Hadro Dominika & Patora-Wysocka Zofia & Fijałkowska Justyna & Mróz-Gorgoń Barbara, 2023. "Sustainability and Fast Fashion from the Executive Perspective – the Case of LPP S.A," Journal of Intercultural Management, Sciendo, vol. 15(3), pages 148-178, September.
  28. Senave, Elseline & Jans, Mieke J. & Srivastava, Rajendra P., 2023. "The application of text mining in accounting," International Journal of Accounting Information Systems, Elsevier, vol. 50(C).
  29. Gopal V. Krishnan & Emma‐Riikka Myllymäki & Neerav Nagar, 2021. "Does financial reporting quality vary across firm life cycle?," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 48(5-6), pages 954-987, May.
  30. Yasheng Chen & Xian Huang & Zhuojun Wu, 2023. "From natural language to accounting entries using a natural language processing method," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(4), pages 3781-3795, December.
  31. Zhang, Chanyuan (Abigail) & Cho, Soohyun & Vasarhelyi, Miklos, 2022. "Explainable Artificial Intelligence (XAI) in auditing," International Journal of Accounting Information Systems, Elsevier, vol. 46(C).
  32. von Zedlitz, Gerrit, 2023. "Mind the gap?! The current state of biodiversity reporting," SAFE White Paper Series 95, Leibniz Institute for Financial Research SAFE.
  33. Miao Liu, 2022. "Assessing Human Information Processing in Lending Decisions: A Machine Learning Approach," Journal of Accounting Research, Wiley Blackwell, vol. 60(2), pages 607-651, May.
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