从社交媒体到股票市场的情绪相关性发现

S. Xie, Manshu Li, Jianxin Li
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引用次数: 1

摘要

社交媒体数据分析已成功应用于许多实际领域,如产品推荐、目标广告等。近年来,它在分析金融趋势或股票营销预测方面也引起了金融研究人员的广泛关注。在本文中,我们的目标是研究揭示股票价格变化与社交媒体数据使用之间相关性的有效方法。在这项工作中,我们首先提供了一种收集 Twitter 数据的机制,使用 Latent Dirichlet Allocation 进行主题建模,然后根据主题进行情感分析,最后发现社交媒体与股价之间的相关性。根据我们的实证结果,我们发现相关性可能会受到讨论流行度和社区价值的影响,而社区价值则代表了待分析和预测的目标公司的幸福感。这可以通过探索市场和危机解决方案来建立。在线社交用户的影响力也在相关性中发挥着重要作用,这是一个操纵因素,应通过衡量其社交媒体账户的责任来考虑有影响力的用户。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Sentiment Correlation Discovery From Social Media to Share Market
Social media data analytics have been successfully applied in many real applications such as product recommendation, target advertisement. In recent years, it also attracted lots of attention from the financial researchers to analyse the financial trending or stock marketing prediction. In this paper, our goal is to investigate the meaningful way of uncovering the correlation between the stock share price change and the social media data usage. In this work, we first provide a mechanism to collect Twitter data, use Latent Dirichlet Allocation for topic modelling, then perform the sentiment analysis based on topics, and finally discover the correlation between social media and share price. Based on our empirical results, we find that the correlation could be impacted by the popularity of discussion as well as the valence of community, which represents the happiness to the target companies to be analysed and predicted. This could be built up by exploring the market and crisis resolution. The influence of online social users also plays a significant role in the correlation, which is a factor of manipulation that the influential users should be considered by measuring the responsibility of their social media account.
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