Tools and Methods for Analysis of Stock Market Manipulation using Social Media : A Longitudinal Characterization of Time Series Dynamics

Sammanfattning: Social media has proven to affect the dynamics of the stock market directly. The potential influence of social media makes it an excellent tool for stock market manipulation, especially in the era of online misinformation. Therefore, the work in this thesis aims to provide a better understanding of company discussion on social media. More precisely, collecting a dataset of company-specific discussion from Twitter, Reddit, Seeking Alpha, and Citron Research enabled us to perform time series analysis using smoothing and clustering, where associated events were identified, categorized, and summarized. A selected companies' time series was also more closely and qualitatively analyzed to build intuition and understanding of the dynamics. The results show that the dynamics of company discussion on social media can be evaluated using the discussion intensities. They also show the possibility of measuring whether a specific social media is, in general, reactive or proactive to abnormal events in the stock market. Moreover, external events seem to trigger discussion activity which propagates through all social media. Furthermore, the results seem to depend on the choice of bandwidth used for smoothing and the number of clusters given to the clustering algorithm, which requires further refinement as a continuation of this thesis.