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The relationship between financial market and information diffusion of social media

This project is a Communication Science research based on Machine Learning and Finance, using big data for time series analysis and text mining. This project will systematically investigate the interaction between social media and the stock markets, which expands the theoretical approaches to information diffusion. This project will start with social media's influence on news of COVID-19 vaccine and then study the difference between the diffusion of information by actors such as organizations, government, media, in types of media channels (mainstream and social media), in types of the markets systems (free markets and socialist markets), in types of industrial systems (raw materials, manufacturing, and service industries), and information diffusion rate in professional media (BBC, CNN). This project will create a new theoretical approach of information diffusion theory and understand stock market volatility to prevent market crashes due to information diffusion.

PhD student: Xin Wang

Supervision team: Tibor Bosse (promoter), Maurice Vergeer (co-promoter)

Funding: Chinese Scholarship Council