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The impact of social media and its influence on the stock market is a popular research topic especially related to Big Data pertaining to social media. The COVID-19 pandemic has affected the stock market in a historical manner. Existing research suggests that COVID-19 hit the financial markets across the globe. In March 2020, the stock market applied the circuit breaker four times to stop the plunge. The inception of the circuit breaker was first designed and used in 1987, and since then, it was used only once (Zhang et al., 2020). Similarly, FTSE, which is the European stock market, plunged 12% in March (Broadstock and Zhang, 2020), and the Japanese stock market plunged 20% since December (Chen, He, and Zhu., 2020). During such unprecedented calamities, investors would like to know how the behavior of the market, and the outlook on future trends, are affected. Sentiments obtained from tweets are a good predictor of the stock market since the investor can get multiple inputs or data points on any given stock or on the overall market in real time. The investors could then use this collective input to plan future investments and forecast earnings. Several studies have documented this finding. Presented below is a literature review of recent studies that examine the influence of user sentiment on predicting the behavior of the stock market.
The current work studies the influence of public sentiment on the behavior of the stock market in the United States of America during this unprecedented COVID-19 pandemic. This study used the Vector Error Correction Model (VECM) to predict the behavior of the stock market based on public sentiment conveyed through tweets. The rest of the paper is organized as follows: Literature Review Data and Methodology, Results, Conclusion, and Future Work.