Evaluating Impact of Social Media Posts by Executives on Stock Prices

TL;DR

This paper explores how social media posts, especially from executives, influence stock and cryptocurrency prices, demonstrating that integrating social media sentiment improves prediction accuracy across multiple assets.

Contribution

It introduces a method to incorporate social media sentiment, particularly executive posts, into stock price prediction models, showing enhanced accuracy over traditional approaches.

Findings

Including social media data improves prediction accuracy.

Executive posts have a greater impact on stock prices.

Results are consistent across stocks and cryptocurrencies.

Abstract

Predicting stock market movements has always been of great interest to investors and an active area of research. Research has proven that popularity of products is highly influenced by what people talk about. Social media like Twitter, Reddit have become hotspots of such influences. This paper investigates the impact of social media posts on close price prediction of stocks using Twitter and Reddit posts. Our objective is to integrate sentiment of social media data with historical stock data and study its effect on closing prices using time series models. We carried out rigorous experiments and deep analysis using multiple deep learning based models on different datasets to study the influence of posts by executives and general people on the close price. Experimental results on multiple stocks (Apple and Tesla) and decentralised currencies (Bitcoin and Ethereum) consistently show improvements in prediction on including social media data and greater improvements on including executive posts.