The researcher compiled a massive 6.3 million-word corpus by comparing the narrative sections of annual reports from companies indicted for fraud against those of legitimate firms.
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Building a computational framework that can automatically screen reports for high-risk linguistic markers. Common Alternatives
Sometimes these numbers correspond to legacy driver sets or firmware updates found on technical repositories. LEGO Sets: Set number
The study, conducted at the University of Stirling , explores how the language used in annual corporate reports (10-K filings) can signal potential fraud.
Identifying whether certain words or phrases used by management can predict financial misstatements before they are officially discovered.
Analyzing 102 "fraudulent" annual reports compared to 306 "non-fraud" reports of similar size and industry.
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