A Data-Driven Framework for Evaluating Positive Language Effects on Stock Volatility Using Text Analytics and Predictive Modelling

In the era of rapid technological advancement, computer technologies such as big data analytics, artificial intelligence, and machine learning have become integral to enterprise operations, driving the wave of digital transformation. These technologies enable enterprises to process vast amounts of data, gain deeper insights into market trends, and make more informed decisions. However, this transformation brings both opportunities and challenges. Nowadays, digital transformation is an inevitable trend in enterprise development. Digital transformation can increase stock volatility, affecting a company’s steady growth. This paper aims to analyze the influence of enterprise digital transformation on stock volatility risk and explore how positive tones from internal managers and positive coverage from external media can mitigate this risk. This paper examines data from Chinese listed companies from 2007 to 2022 and finds that digital transformation can elevate stock market volatility risks. Internal positive managerial tone and external positive media coverage can mitigate the negative influence of digital transformation on stock market volatility risks. This study offers a novel theoretical perspective on enterprise risk management. Traditional risk management theories typically emphasize internal controls within organizations. Differently, this study integrates the perspectives of internal managers and external media into the research framework of risk management, broadening the scope of risk management research. It offers a novel theoretical framework and practical recommendations for organizations to effectively navigate risks in the context of digital transformation.