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Predicting Stock Prices Using Tweet Frequency and AI: Leveraging Social Media Insights to Forecast Tomorrow's Market Trends

Authors

Zimo Liu1, Lin Yang1 and Tami Takada2, 1USA, 2California State Polytechnic University, USA

Abstract

I use the frequency of the tweet counts of the stock ticker to predict the stock price [1]. Using AI to predict the price with today’s tweet count and the highest and lowest stock price to predict tomorrow’s stock price [2]. The benefits of predicting stock prices are minimizing losses and getting a better idea about making money. But since the price of stocks is hard to predict, analyzing the number of price tickers discussed in social media can help people to know more precisely trends. “They analyzed the activity of 150 companies chosen at random from the S&P 500 Index and noticed a correlation between the number of tweets they sent and their share price [3]. Having observed this, the researchers devised a mathematical model, applied it to an imaginary portfolio and outperformed other financial strategies based on financial analysis by as much as 11%” [4]. This indicates the reliability of predicting stock prices with social media. Compared with some popular methods such as Auto-Regressive Conditional Heteroscedastic or Generalized Auto-Regressive Moving Average, using social media to predict price can consider the effect of social trends on the stock price [5]. Using social media to predict the stock price is not subjective and is much cheaper to computerize.

Keywords

Stock Price Prediction, Tweet Frequency Analysis, AI-Based Forecasting, Social Media Trends