This study presents a method to analyse social media interactions and their relationship with investor decisions and stock market movements. It explores three questions: (1) the best method for classifying stock-related social media posts, (2) the influence of posts on stock returns and trading volumes, and (3) the impact of posts by opinion leaders. WallstreetBets board in Reddit social media and the GameStop stock provide an ideal laboratory for answering these questions. We analysed 135,000 posts, 5.6 million comments, and 90,000 users from November 2020 to June 2021. Using natural language processing and deep learning, posts and comments were classified by user intention (buy, sell, hold). We found that a BERT-based classifier achieved the highest performance with an F1 score of 80.2%. We then analysed the relationship between social media activity and stock market data, finding that posts are related to trading volumes but not stock returns. However, considering the popularity of posts, there is a significant relationship between social media opinions and stock returns and trading volumes. The study highlights the importance of "influencers": posts from a few influential users significantly impact stock returns and volumes. This research underscores the importance of social media dynamics in financial market behaviour.
Bongini et al. (Fri,) studied this question.