Evaluating Impact of Social Media Posts by Executives on Stock Prices

Anubhav Sarkar, Swagata Chakraborty, Sohom Ghosh, Sudipta Naskar
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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.
评估高管在社交媒体上发帖对股价的影响
预测股市走势一直是投资者非常感兴趣的话题,也是一个活跃的研究领域。研究证明,产品的受欢迎程度很大程度上受到人们谈论的内容的影响。Twitter、Reddit等社交媒体已经成为此类影响的热点。本文利用Twitter和Reddit帖子研究了社交媒体帖子对股票收盘价预测的影响。我们的目标是将社交媒体数据的情绪与历史股票数据相结合,并使用时间序列模型研究其对收盘价的影响。我们在不同的数据集上使用多个基于深度学习的模型进行了严格的实验和深度分析,以研究高管和一般人的帖子对收盘价的影响。对多只股票(苹果和特斯拉)和去中心化货币(比特币和以太坊)的实验结果一致表明,在包括社交媒体数据的预测方面有所改善,在包括高管职位的预测方面有更大的改善。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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