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Emergency public opinion evolution analysis method based on sentiment analysis and theme features

A technology for emergency and emotion analysis, applied in the fields of instruments, electrical digital data processing, data processing applications, etc., can solve problems such as no mathematical model, no discovery plan, etc., to avoid the phenomenon of emotional polarization.

Pending Publication Date: 2020-01-24
TIANJIN UNIV
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Problems solved by technology

In recent years, although some scholars have conducted in-depth analysis of the characteristics of public opinion and given some definitions of key points of public opinion, they have not given a specific mathematical model, nor have they proposed a feasible discovery plan, and most of the discovery methods are manual collection. tidy

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  • Emergency public opinion evolution analysis method based on sentiment analysis and theme features
  • Emergency public opinion evolution analysis method based on sentiment analysis and theme features
  • Emergency public opinion evolution analysis method based on sentiment analysis and theme features

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Embodiment

[0073] figure 2 Dynamic topic model (DTM) process, where z is the hidden variable (ie topic) corresponding to each word in the corpus, θ is the topic distribution of each document, is the word distribution for each topic, randomly initialized z, θ and It can be obtained by likelihood estimation.

[0074] Take the Weibo emergency "Zika virus" as an example. First, the time series public opinion evolution trend curve of Zika virus events on Weibo is calculated, as shown in image 3 shown. It can be seen from the figure that the Zika virus incident began to appear on September 30, 2016. Over time, the number of microblogs on this topic continued to increase, and there was a sharp increase on October 8 and October 13. It peaked on October 18.

[0075] Using the network public opinion evolution method based on sentiment analysis, the Zika virus data is time-sliced ​​based on the sentiment value and text similarity respectively, and the keyword popularity analysis is carried...

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Abstract

The invention discloses an emergency public opinion evolution analysis method based on sentiment analysis and theme features. The emergency public opinion evolution analysis method mainly comprises the steps: firstly carrying out the word segmentation of a data text through employing a word segmentation method based on character string matching according to the features of Chinese word segmentation; secondly, utilizing synonym linguistic data to extend weights and features of words after word segmentation, and calculating emotion values; then calculating and carrying out time slicing on the data based on the emotion difference value; and finally, taking the data after the time slicing as the input of a dynamic topic model (DTM) so as to obtain the change and the popularity of the topic word of the emergency in a time sequence, predicting the development trend of the emergency, and verifying the effect of sentiment analysis in a topic evolution process by comparing with a topic evolution result only considering the text similarity slicing.

Description

technical field [0001] The invention belongs to the field of natural language processing, and specifically relates to a method for analyzing the evolution of emergency public opinion of emotional analysis and theme features, which is to excavate the emotions expressed by netizens under emergency events. Background technique [0002] At present, the traditional method of studying the changes in the observed values ​​of the number of comments on public opinion to obtain the development trend of public opinion, although the time series analysis directly takes the observation data corresponding to the state of things at different moments as the research object, through analysis And study the characteristics of time series data to establish a time series model, and then discover and describe the law of things that change over time on the basis of the fitted model. For the analysis of time series, researchers have accumulated some classic methods, which mainly include model method...

Claims

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Application Information

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IPC IPC(8): G06F40/289G06F40/247G06Q50/00G06Q50/26
CPCG06Q50/01G06Q50/26
Inventor 孙越恒杨宇杰
Owner TIANJIN UNIV
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