Online public opinion emergency automatic identification method based on emotion information extraction and analysis

Abstract

The invention provides a network public opinion emergency automatic identification method based on emotion information extraction and analysis. The method comprises the steps of obtaining massive social media data according to a social media collection method, and performing data preprocessing such as data filtering and cleaning; training an emotion model according to the historical social media data to form an emotion recognition model; detecting and analyzing sudden emotions in the social media according to the emotion recognition model; extracting social media tags corresponding to the sudden emotions, and recognizing event original keywords of the tags corresponding to the sudden emotions through word segmentation processing to form an event original keyword library; and extracting social media event keywords, matching the social media event keywords with the keyword library, and when the keywords are completely matched and the emotion state is not negative, obtaining correspondingevent basic information to form emergency description. The invention is suitable for identifying various social media emergencies, high in expandability, good in reusability and low in development cost, and can be applied in multiple dimensions according to service requirements.

Description

technical field [0001] The invention relates to the fields of natural language processing and big data analysis, in particular to an automatic identification method for network public opinion emergencies based on emotional information extraction and analysis. Background technique [0002] The continuous advancement of Internet technology has led to the vigorous development of social networks. The number of users of social networking platforms such as Sina, Weibo, and Facebook is increasing day by day. Users share short and real-time information through the attention mechanism by posting relevant news events, views or personal dynamics, which has a certain Timeliness and wide dissemination. A large amount of social network information contains users' opinions and attitudes on related events. Through in-depth analysis of such data, users' emotional tendencies and implicit information can be identified. The relevant analysis results can help the government understand the public...

AI Technical Summary

Problems solved by technology

[0004] In order to solve the above-mentioned problem that the above-mentioned social network platform has a large workload for identifying emergencies through event extraction and is not effective in identifying

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