Emoji text sentiment analysis method and system based on deep learning

Abstract

The invention discloses an emoji text sentiment analysis method and system based on deep learning. The method comprises the steps of 1, collecting an independent user generation text with emoji; 2, screening the independent user generated texts to obtain an original data set; 3, carrying out the vector packaging of three dimensions of series, class and vels on the original data set, and obtaining a label; 4, dividing the series vectors, the corresponding class vectors, the corresponding vels vectors and the corresponding labs into a training set, a verification set and a test set according to a proportion; 5, constructing an emoji text sentiment analysis model; 6, inputting the vectors of the series, the class and the vels of the training set and the labs into an emoji text sentiment analysis model for training; 7, inputting the test set into the trained emoji text sentiment analysis model, and then carrying out clustering to obtain a final result. The invention also discloses a system corresponding to the disclosed method. According to the method, any prior understanding on emoji is not introduced, the original emotion information of the text is fully reserved without any damage, and the disclosed model is more accurate and higher in subdivision degree compared with an existing model.

Description

technical field [0001] The invention belongs to the technical field of natural language processing, and in particular relates to a deep learning-based emoji text emotion analysis method and system Background technique [0002] In the field of natural language processing, many tasks, especially text classification and sentiment analysis, are severely limited by the lack of labeling of corpus data, and the cost of manual labeling is high. With the rise of social media, emoticons such as emoji have begun to sweep the world. In the text of social platforms such as Weibo, QQ, WeChat, Twitter, etc., users often use emoji instead of text to express their emotions, so emoji is used in text It can play a very important role in understanding and text sentiment analysis. For the problem of "lack of annotations in the corpus", in the text with emoji, the existence of emoji is equivalent to the user's own annotation of the emotional attitude of the text, so we are equivalent to directly...

AI Technical Summary

Problems solved by technology

[0002] In the field of natural language processing, many tasks, especially text classification and sentiment analysis, are severely limited by the lack of labeling of corpus data, and the cost of manual labeling is very high

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