Public opinion data analysis model based on deep learning

A sentiment analysis and model technology, applied in the field of multi-task text data analysis, can solve the problems of low efficiency of public opinion data processing, difficulty in discovering the development trend of public opinion events and hot topics in time, so as to prevent over-fitting, improve efficiency, and improve The effect of processing efficiency

Inactive Publication Date: 2020-10-30
SUN YAT SEN UNIV
View PDF2 Cites 2 Cited by
  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

However, the existing monitoring system simply retrieves relevant information, and it is difficult to discover the development trend and hot topics of public opinion events in time, and the processing efficiency of public opinion data is low.

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
  • Public opinion data analysis model based on deep learning
  • Public opinion data analysis model based on deep learning
  • Public opinion data analysis model based on deep learning

Examples

Experimental program
Comparison scheme
Effect test

Embodiment Construction

[0030] The present invention will be further described below in conjunction with the accompanying drawings.

[0031] This application discloses a multi-task text analysis method based on CNN-LSTM-based text sentiment analysis and word2vector-based textrank summary automatic extraction, in which the number of texts is large and the content is complex, including questions and answers, comments in various aspects, and some speeches Attitude and article gist are not clear, the text data processing model among the present invention comprises convolutional neural network (CNN), long short-term memory network (LSTM) and softmax classifier, and word2vector word embedding model and textrank summary extraction model.

[0032] The method disclosed in the present invention is a text data analysis method used in a public opinion monitoring system, and the main flow and structure of data acquisition and analysis refer to figure 1 . The method combines CNN-LSTM to analyze public opinion tex...

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 relates to a multitask text analysis method based on text sentiment analysis of CNN-LSTM and textrank abstract automatic extraction of word2vector. The method comprises the steps of obtaining massive to-be-tested network text data, firstly, preprocessing network text data to be tested and then inputting the preprocessed network text data into an LSTM-CNN neural network; according tothe LSTM-CNN, a classical text sequence processing method being used for a long-term and short-term memory network; obtaining a vector representing the context; the CNN further extracting higher-dimensional and effective features; then, sending features into softmax to be subjected to multi-classification, so that sentiment positive and negative directions of a text are obtained, secondly, segmenting the input text data into sentences by combining a textrank algorithm based on word embedding to construct a graph model, and calculating the similarity between the sentences to serve as weights ofedges; by calculating sentence scores, sorting the obtained sentence scores in an inverted order, and extracting several sentences with the highest importance degree as candidate abstract sentences;finally, displaying the analysis result in the form of a report. The multi-task text data processing model enables a public opinion monitoring result to obtain high accuracy and high efficiency, and text analysis precision is improved by using two neural network training.

Description

technical field [0001] The invention relates to the field of network public opinion text data processing, in particular to a multi-task text data analysis method based on CNN-LSTM text sentiment analysis and word2vector textrank summary automatic extraction. Background technique [0002] Internet public opinion refers to a network method in which people discuss social hot topics through common Internet communication channels, such as news websites, Weibo, Zhihu, and Douban. It mainly has the characteristics of convenient and fast communication. . [0003] In the era of big data, online media has penetrated into people's daily life. Public opinion monitoring achieves user public opinion monitoring by using automated tools to capture massive amounts of information, sentiment classification, and news special attention, forming reports and charts to present trends. However, the existing monitoring system simply retrieves relevant information, and it is difficult to find the de...

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
Patent Type & Authority Applications(China)
IPC IPC(8): G06F40/289G06F40/284G06F40/211G06F40/216G06F16/35G06F16/901G06N3/04G06N3/08
CPCG06F40/289G06F40/284G06F40/211G06F40/216G06F16/355G06F16/9024G06N3/049G06N3/08G06N3/045
Inventor 况丽娟管亦铮戴宪华
Owner SUN YAT SEN 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