Exploring the Impact of Social Media Sentiment on Market Dynamics and Economic Growth: A Big Data and Natural Language Processing Perspective
摘要
Social media’s introduction has completely changed how information is shared and how it affects international marketplaces. With an emphasis on well-known platforms like Facebook and Twitter, this paper examines the regulatory framework put in place by the European Union (EU) to oversee the markets for digital platforms. The study highlights how sentiment analysis has become essential for comprehending market dynamics and economic progress, drawing on developments in big data analytics and natural language processing (NLP). Important conclusions emphasize how the Digital Markets Act (DMA) and Digital Services Act (DSA) promote openness and competition while tackling issues like false information and market volatility. The study also looks at the ramifications of real-time sentiment monitoring for corporations and governments, as well as the predictive ability of NLP models in financial decision-making. This study adds to the expanding corpus of research at the nexus of platform governance, economic policymaking, and social media sentiment.