Emoji text sentiment analysis method and system based on deep learning

A technology of sentiment analysis and deep learning, applied in text database clustering/classification, semantic analysis, unstructured text data retrieval, etc., can solve problems such as high cost of manual labeling, lack of labeling of corpus data, etc., to improve accuracy and High degree of refinement, high degree of refinement, and accurate model effect

Pending Publication Date: 2021-12-07
NANJING UNIV
View PDF0 Cites 0 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0002] In the field of natural language processing, many tasks, especially text classification and sentiment ana

Method used

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
View more

Image

Smart Image Click on the blue labels to locate them in the text.
Viewing Examples
Smart Image
  • Emoji text sentiment analysis method and system based on deep learning
  • Emoji text sentiment analysis method and system based on deep learning
  • Emoji text sentiment analysis method and system based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Example Embodiment

[0052] DRAWINGS The present application will be further described below in conjunction. The following examples serve only to more clearly illustrate the technical solutions of the present invention, and are not intended to limit the scope of the present application.

[0053] The present invention discloses a emoji sentiment analysis method based on the depth of learning, the processes which Figure 5 As shown, the method includes the following steps:

[0054] Step 1: acquisition of individual users with emoji generate text;

[0055] User to independently generate text refers to text semantics with other single text messages context relationship information is not present, and the entry of text information is not referenced or embedded media links or other text information. Including user posted on the Internet has a time stamp of the text information, including blog, microblogging, micro-channel circle of friends information. Such as social media chat is not independent of user-gen...

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

PUM

No PUM Login to view more

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...

Claims

the structure of the environmentally friendly knitted fabric provided by the present invention; figure 2 Flow chart of the yarn wrapping machine for environmentally friendly knitted fabrics and storage devices; image 3 Is the parameter map of the yarn covering machine
Login to view more

Application Information

Patent Timeline
no application Login to view more
IPC IPC(8): G06F16/35G06F40/30G06N3/04
CPCG06F16/35G06F40/30G06N3/045Y02D10/00
Inventor 胡广伟艾文华
Owner NANJING UNIV
Who we serve
  • R&D Engineer
  • R&D Manager
  • IP Professional
Why Eureka
  • Industry Leading Data Capabilities
  • Powerful AI technology
  • Patent DNA Extraction
Social media
Try Eureka
PatSnap group products