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8 May 2023 LDA-Bert based public opinion subject mining analysis of emergencies
Tiantian Liu, Xiaoyan Gu
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Proceedings Volume 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023); 126350T (2023) https://doi.org/10.1117/12.2679263
Event: International Conference on Algorithms, Microchips, and Network Applications 2023, 2023, Zhengzhou, China
Abstract
Studying the theme of emergencies is of great significance to the emergency management of subsequent public opinion. In order to solve the problem that LDA ignores the context semantics, and the topic distribution is biased towards high-frequency words, Bert is introduced. LDA-Bert public opinion topic mining model is proposed. First, LDA is used to select candidate words; Then, Bert is used to construct candidate word vectors and topic vectors with context semantics, and the topic keywords are filtered twice by cosine similarity calculation; Finally, the corresponding public opinion response strategies are proposed through the subject mining results of different life cycles. Taking the "Xi'an epidemic" as an example, the experiment proved that the model can effectively extract theme keywords, providing a strong basis for the follow-up analysis of theme changes at different stages of public opinion.
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Tiantian Liu and Xiaoyan Gu "LDA-Bert based public opinion subject mining analysis of emergencies", Proc. SPIE 12635, Second International Conference on Algorithms, Microchips, and Network Applications (AMNA 2023), 126350T (8 May 2023); https://doi.org/10.1117/12.2679263
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KEYWORDS
Mining
Emotion
Semantics
Feature extraction
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