A method for constructing emotion recognition model of Chinese social text based on deep fusion neural network

Abstract

The invention discloses a method for constructing a Chinese social text emotion recognition model based on a deep fusion neural network, which comprises the following steps: data collection, using a Python Scrapy framework to construct a social text network crawler, and collecting picture and text data; Data preprocessing, preprocessing the Chinese text collected by the data acquisition module; Data annotation for emotionally annotating the processed text; Text vectorization, using Word2Vec tools to train the word vector; Model building, design integration BILSTM-CNN network model; Model training, will be marked after the text through BILSTM-CNN fusion neural network model for training. The invention constructs a deep fusion emotion analysis model, aiming at making full use of the featureextraction ability of the depth neural network model to carry out feature expression on Chinese emotion text, thereby constructing a multi-classification model of emotion, and improving the accuracy rate of automatic emotion multi-classification.

Description

technical field [0001] The invention relates to the technical field of natural language processing, in particular to a method for constructing a Chinese social text emotion recognition model based on a deep fusion neural network. Background technique [0002] Sentiment analysis belongs to the sentiment analysis class of problems. Sentiment analysis (SA), also known as tendency analysis and opinion mining, is a process of analyzing, processing, inducing and inferring emotionally subjective texts. Sentiment analysis can be applied to many fields such as e-commerce, brand reputation management, and public opinion analysis. With the popularity of social media such as Weibo, users discuss the products and services they use, or express their political and religious views, and Weibo sites have become a valuable source of people's comments and emotional information. Sentiment analysis on such data has now attracted extensive attention from researchers. [0003] So far, most micro...

AI Technical Summary

Problems solved by technology

In the existing technology, there is a lack of more detailed analysis of the emotional characteristics of Chinese texts, and the analysis of the characteristics of convolutional neural networks and long-short-term memory networks. Therefore, it is urgent to study how to use deep learning fusion models to achieve better Chinese emotion classification results.

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