Microblog emotion analysis method based on standard dictionaries and semantic rules

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.

Description

technical field [0001] The invention belongs to pattern recognition methods, in particular to a microblog emotion analysis method based on standard dictionaries and semantic rules. Background technique [0002] With the rapid development of network technology and the emergence of social media, network users experience unprecedented convenience. Social media (such as Facebook, Twitter, Sina Weibo, etc.) provide users with a platform for sharing information and publicly expressing personal opinions. With the huge amount of Weibo data behind it, there is a lot of information behind it. If these data can be effectively used, it can be Obtain huge potential value: for consumers, the summary analysis of certain types of product reviews can provide them with purchasing references; for commercial companies, analyzing product reviews can be used as the basis for their subsequent marketing strategy improvement; for government departments It is said that mastering the development of p...

AI Technical Summary

Problems solved by technology

However, in the process of analyzing sentiment, traditional algorithms still face some important problems to be solved: 1) Although the semantic sentiment analysis algorithm can isolate words from sentences, it ignores the contextual relationship and syntactic rules of words; 2) Although the method based on machine learning is effective in processing long texts such as news and forums, the analysis effect on short texts on Weibo is not ideal.

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