Emotion classification model training and textual emotion polarity analysis method and system

Abstract

The invention provides an emotion classification model training and textual emotion polarity analysis method and system. The emotion classification model training method comprises the steps that data are acquired from a corpus so that original data are obtained; the original data are preprocessed so that preprocessed data are obtained; word vectors are extracted from the preprocessed data through a neural network model; the word vectors are fused according to preset fusion rules so that sentence vector characteristics are generated; and an emotion classification model is trained according to the sentence vector characteristics so that the trained emotion classification model is obtained. The neural network model is adopted, the words are expressed by low-dimensional spatial vectors, the low-dimensional spatial word vectors are fused into the sentence vector characteristics according to the preset rules, and the emotion classification model is obtained by certain learning models through training so that word vector dimension can be effectively reduced, the dimensions disaster problem can be avoided, correlative attributes between the words can be mined and vector semantic accuracy can be enhanced.

Description

technical field [0001] The invention relates to the technical field of data mining, in particular to a method and system for training an emotion classification model and a method and system for analyzing text emotion polarity. Background technique [0002] Sentiment analysis, also known as tendency analysis, is the process of analyzing, processing, summarizing and reasoning subjective texts with emotional color. Common sentiment analysis includes opinion extraction, opinion mining, sentiment mining, and subjective analysis. [0003] In terms of financial information analysis, investors have long recognized that financial markets are easily driven by human nature such as fear and greed, but there is a lack of technology or data to objectively and comprehensively quantify people's specific emotions. Sentiment analysis of social data opens a window to understand the spiritual world for investors who have been troubled by irrational actions in the financial market, and predicts...

AI Technical Summary

Problems solved by technology

Because the word vector sparse representation often encounters the curse of dimensionality when solving practical problems, and the semantic information cannot be represented, and the potential connection between words cannot be revealed.

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