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| Investor Sentiment Mining Based on Bi-LSTM Modeland Its Impact on Stock Price Bubbles |
| YIN Haiyuan，YANG Qingsong |
| Shaanxi Normal University, Xi’an, China |
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Abstract In order to explore the influence and prediction ability of investor sentiment on stock price bubble, this study constructs a two-way long-short-term memory model to identify the sentiment polarity of real-time posting texts of sample stocks, and constructs the daily investor sentiment index. Further, based on the General Sup ADF method, the stock price bubble is tested and the relationship between investor sentiment and stock price bubble is empirically studied. The empirical results show that investor sentiment has a positive effect on the probability and strength of stock bubble; This effect is more significant in small-scale, low equity concentration and non-state-owned enterprises; The mediation test shows that investor sentiment has an impact on stock price bubble through current transaction amount of the stock.
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Received: 27 January 2022
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