Microblog emotion analysis method based on standard dictionaries and semantic rules

Through the Weibo sentiment analysis method based on standard dictionaries and semantic rules, combined with sentence patterns and inter-sentence relationships, it solves the problem of traditional methods ignoring the contextual relationships of words, improves the classification accuracy and accuracy of Weibo sentiment analysis, and is suitable for microblog applications. Sentiment analysis of short blog posts.

CN106202584AInactive Publication Date: 2016-12-07BEIJING UNIV OF TECH
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Patent Information

Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
BEIJING UNIV OF TECH
Filing Date
2016-09-20
Publication Date
2016-12-07
Estimated Expiration
Not applicable · inactive patent

AI Technical Summary

⚠Technical Problem

Traditional Weibo sentiment analysis methods ignore word context and syntactic rules, and the analysis effect on Weibo short texts is not ideal, reflecting the incomplete emotional tendency of Weibo information.

⚗Method used

A Weibo sentiment analysis method based on standard dictionaries and semantic rules is used to calculate Weibo sentiments through a computational model of sentiment dictionaries plus semantic rules, and the emoticon dictionary is used to correct the results to improve the classification accuracy of sentiment tendency analysis, taking into account sentence structure relationships and sentence structure. Relationship between expressions and text for sentiment analysis.

🎯Benefits of technology

It improves the classification accuracy of positive, negative and neutral emotional data, can adaptively handle complex Chinese semantic situations, and improves the accuracy and recall rate of Weibo sentiment analysis.

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Abstract

The invention discloses a microblog emotion analysis method based on standard dictionaries and semantic rules. The microblog emotion analysis method comprises the following steps: collecting microblog data and manually labeling and marking the emotion value of each microblog; proposing corresponding standard micrblog emotion dictionaries, and establishing an emotion dictionary database; based on the standard emotion dictionaries, adding the semantic rules for assistance, and performing parameter adjustment and optimization on parameters of the semantic rules; based on a real dataset experiment, acquiring the final classification accuracy and precision. The technical scheme provided by the invention is adopted to well analyze the emotion tendency of each microblog user by introducing the standard emotion dictionaries, microblog expression dictionaries and the semantic rules, therefore, higher classification accuracy and precision are achieved.
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