社交媒体大数据、投资者情绪与IPO抑价

Social Media Big Data,Investor Sentiment and IPO Underpricing

为深入研究社交媒体大数据中所反映的投资者情绪与IPO(Initial Public Offerings)抑价之间的关系,采用网络爬虫(Python)技术挖掘社交媒体大数据,通过人工构建股市情绪词库,分析了社交媒体言论中包含的投资者情绪与IPO抑价之间的关系。结果表明:社交媒体大数据中的投资者积极情绪与IPO抑价存在显著正相关关系;消极情绪与IPO抑价呈显著负相关关系,且消极情绪对IPO抑价率的影响更为显著。研究结论表明,社交媒体大数据可以作为衡量投资者情绪的可靠指标,为度量投资者情绪提供了新方法,并为监管机构对社交媒体信息及水军的靶向性监管提供了可借鉴的理论基础。

Social media provides an opener platform for individual investors to express opinions and gather information.In order to study the relationship between investor sentiment and IPO underpricing deeply,web crawler(Python)technology is used to mine social media big data,and a stock market emotional lexicon is manually constructed to analyze investor sentiment and IPO underpricing included in social media speeches.The results show that the positive sentiment of investors of the social media big data has a significantly positive correlation with IPO underpricing,the negative sentiment of investors has a significantly negative correlation with IPO underpricing,and negative sentiment has a more significant effect on IPO underpricing rate.Further research shows that social media big data can be used as a reliable index to measure investor sentiment,which provides new methods for measuring investor sentiment and lays the theoretical foundation for government′s regulation on social media information.