挖掘 COVID-19 情绪与市场表现之间的关系
Mining the Relationship Between COVID-19 Sentiment and Market Performance
AI总结：
本文利用 Twitter 文本情感分析提取 COVID-19 相关情绪，发现其与疫情初期股市表现具有强关联，并可作为未来市场预测指标。
摘要：
在 3 月 COVID-19 疫情暴发之初，我们观察到历史上最大规模的股市暴跌之一。在此后的几个月内，市场经历了波动的看涨回升，恢复到疫情前的表现水平，甚至更高。本文研究 COVID-19 疫情最初几个月期间股市行为与 COVID-19 情绪之间的关系。通过对 Twitter 数据进行文本情感分析，我们考察包含与 COVID-19 疫情相关关键词的推文及其情绪，以了解情绪是否能够用作股市表现的指标。此前已有研究将自然语言处理和文本情感分析应用于理解股市表现；鉴于 COVID-19 对经济影响的普遍程度，我们希望进一步应用这些技术，以理解 COVID-19 与股市表现之间的关系。研究结果表明，推文中得出的 COVID-19 情绪与股市表现存在很强的关联，可用于预测未来的股市表现。
英文摘要：
At the beginning of the COVID-19 outbreak in March, we observed one of the largest stock market crashes in history. Within the months following this, a volatile bullish climb back to pre-pandemic performances and higher. In this paper, we study the stock market behavior during the initial few months of the COVID-19 pandemic in relation to COVID-19 sentiment. Using text sentiment analysis of Twitter data, we look at tweets that contain key words in relation to the COVID-19 pandemic and the sentiment of the tweet to understand whether sentiment can be used as an indicator for stock market performance. There has been previous research done on applying natural language processing and text sentiment analysis to understand the stock market performance, given how prevalent the impact of COVID-19 is to the economy, we want to further the application of these techniques to understand the relationship that COVID-19 has with stock market performance. Our findings show that there is a strong relationship to COVID-19 sentiment derived from tweets that could be used to predict stock market performance in the future.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
