Despite milk's crucial role in promoting national health and food security, few studies have explored milk-related reporting issues in the news media. This study aims to provide a comprehensive view of various milk-related stakeholders' perspectives by analyzing news big data. We conducted semantic network analysis and topic modeling using generative AI on 1,338 milk consumption-related news articles from the past five years. The analysis identified positive topics such as consumer health, food safety, pricing policies, reusable packaging, sustainable consumption and the subscription economy, new product development in the protein market, and efficiency in logistics and distribution systems. Notably, the increase in organic milk and dairy product consumption and the positive impact of coffee and milk combinations on milk consumption were significant issues. Conversely, negative issues included declining milk consumption, the rise of plant-based alternatives, increasing milk prices, low birth rates and demographic changes, and decreased consumption due to COVID-19. By tracking changes in specific keywords and positive/negative issues related to milk consumption highlighted by the news media over the past five years, this study presents both the challenges and opportunities facing the milk industry. It is expected to provide insights for developing multifaceted milk consumption promotion strategies for policymakers, dairy farmers, consumers, and media professionals in the milk industry.