Abstract
Online public opinion has a strong social influence and spreads at a very fast speed. Public opinion analysis on financial public opinion reports is conducive to the relevant institutions to conveniently understand the public opinion of the event and make correct guidance and control, which is also conducive to the sustainable development of financial market. In this paper, subject model, emotion dictionary construction, public opinion analysis and other technologies are used to conduct a detailed study of financial related network public opinion, and a financial public opinion analysis model is designed. The model can effectively identify the emotional words in the text from the improved topic model, and then match the emotional words with the more comprehensive and perfect emotional dictionary in the financial field, calculate the emotional tendency value of the emotional words, so as to classify the financial text public opinion more accurately.
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Wang, X., Wu, Z. (2021). Qualitative and Quantitative Analysis of Financial Public Opinion Risk Based on Big Data Analysis. In: Abawajy, J., Xu, Z., Atiquzzaman, M., Zhang, X. (eds) 2021 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2021. Advances in Intelligent Systems and Computing, vol 1398. Springer, Cham. https://doi.org/10.1007/978-3-030-79200-8_129
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DOI: https://doi.org/10.1007/978-3-030-79200-8_129
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