上市公司数字技术风险暴露数据（2007-2024年）

Group 1 - The article discusses the exposure of listed companies to digital technology risks from 2007 to 2024, utilizing FinBERT, a large language model, to analyze the Management Discussion and Analysis (MD&A) sections of annual reports for sentiment related to digital technology security [2][3] - The methodology involves identifying relevant text on digital technology risks, constructing a keyword list based on existing guidelines, and extracting sentences that reflect these risks [3][4] - A training dataset is created by annotating a sample of sentences to determine whether they indicate risk exposure or preventive measures, using a combination of AI models for accuracy [4][5] Group 2 - The final exposure level of digital technology risk is defined as the difference between the maximum negative sentiment probability of disclosed risks and the average positive sentiment probability of preventive measures, leading to the creation of specific indicators for data security and cyber risk exposure [6] - The effectiveness of the digital technology risk exposure indicators is validated by examining their correlation with other types of risks, revealing a significant positive relationship with financial and operational risks [7][8] - The model's accuracy in sentiment analysis related to digital technology risks is confirmed through random sampling and manual review, demonstrating high performance, especially in clearly biased sentences [8]