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Impacts of “Poster-Follower” Sentiment on Stock Market Performance |
Zhang Ning, Yin Lemin(), He Lifeng |
School of Business, Qingdao University, Qingdao 266071, China |
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Abstract [Objective] The paper investigates the relationship between the “Bullish Sentiment Index” (BSI) of online reviews/following comments and the performance of stock market. [Methods] First, we conducted sentiment classification for comments on Shanghai Stock Exchange Composite Index using semantic analysis method. Then, we built the sentiment tendencies of these reviews and constructed their “Poster-Follower” BSI. Finally, we used linear and nonlinear models to examine the proposed method empirically. [Results] The BSI based on our proposed method (text mining) could effectively predict the stock market trend, especially on its returns. [Limitations] We only consider two emotional polarities and more research is needed to enhance the sentimental strength. [Conclusions] The Bullish Sentiment Index could effectively predict the overall stock market trend by measuring investors’ sentiment.
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Received: 22 November 2017
Published: 11 July 2018
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