Microblog sentiment analysis method based on large-scale corpus characteristic learning

Abstract

The invention discloses a microblog sentiment analysis method based on large-scale corpus characteristic learning. The method is characterized in that microblog texts is used to train a neural network based on Word2Vec, the neural network completes training by inputting the microblog texts, the neural network maps the input microblog to a corresponding word vector according to grammar contents, emotional tendency of current contents, and whether words are denied or not, and a matrix formed by word vectors corresponding to the words in the microblog is obtained. Synthesis of word vectors is performed on the matrix, so as to further obtain a feature vector corresponding to the microblog. Through applying the feature vector to training and prediction of a sentiment classification device, a relatively accurate microblog sentiment analysis is obtained. Compared with the prior art, the method is low in cost and high in analysis accurate rate, and is especially suitable for large-scale corpus, and is fast in training speed. Combining with grammar contents and emotional tendency, the method effectively processes negation relations, and improves accurate rate of sentiment analysis.

Description

technical field [0001] The invention relates to the technical field of Internet information search, in particular to a microblog sentiment analysis method based on large-scale corpus feature learning. Background technique [0002] In today's information explosion, Weibo, as a social tool, has an increasing impact on people's lives. No matter what you do, see, or hear, you want to share it with others. Weibo provides such a platform, allowing users to freely share their thoughts, experiences, etc. with others. Weibo sentiment analysis refers to the extraction and analysis of opinions in Weibo. For example, for a Weibo that contains comments on a certain movie, Weibo sentiment analysis is to analyze the comments on this movie in this Weibo. Emotional orientation, that is, judging whether the point of view is positive or negative (classification problem). Since the microblog platform carries a large number of subjective thoughts of users, automatic sentiment analysis on micro...

AI Technical Summary

Problems solved by technology

[0004] Existing microblog sentiment analysis methods require manual design of features, heavy workload, high cost, and complex network structure. They cannot combine grammatical, contextual, and emotional tendencies to effectively deal with negative relationships, and the accuracy of sentiment analysis is low.

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