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A Method for Emotional Evolution Analysis of Microblog Topics

An analysis method and theme technology, applied in special data processing applications, instruments, electronic digital data processing, etc., can solve the emotional integration, cannot effectively capture the theme's emotional evolution trend, and consider the theme and emotional evolution mechanism from the perspective of time dimension, etc. problems, to achieve the effect of enhancing network cultural security, improving the quality of active information services, and overcoming subject preference and viewpoint drift.

Inactive Publication Date: 2018-08-17
FUJIAN NORMAL UNIV
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Problems solved by technology

[0014] From the above analysis, it can be seen that the existing LDA topic emotion model does not consider the evolution mechanism of topics and emotions from the perspective of time dimension, and the existing LDA topic evolution model does not integrate emotions well, both of which may lead to Unable to effectively capture the emotional evolution trend of topics hidden in Weibo messages

Method used

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  • A Method for Emotional Evolution Analysis of Microblog Topics
  • A Method for Emotional Evolution Analysis of Microblog Topics
  • A Method for Emotional Evolution Analysis of Microblog Topics

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Embodiment Construction

[0038] The present invention will be further described in detail below in conjunction with the drawings and specific embodiments. In order to better describe the technical solution of the present invention, the relevant symbols of the technical solution of the present invention are now listed in a list, see Table 1.

[0039] Table 1 Model symbol description

[0040]

[0041] In order to facilitate the detailed description of the present invention, the LDA topic model and the emotional periodicity theory are first introduced.

[0042] LDA is an unsupervised machine learning technology that can be used to identify hidden subject information in large-scale document collections. It uses a bag of words representation method, which treats each document as a word frequency vector, thereby transforming text information into mathematical objects that are easy to model. Each document represents a probability constituted by some topics Distribution, and each topic represents a probability dis...

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Abstract

The invention relates to a microblog theme emotion evolution analysis method, comprising the following steps of: step 1.setting circulation control parameters C1, C2, C3 and C4, and an emotion dictionary; step 2. initializing a emotional polarity and a theme attribution of a word in a microblog message set; step 3. computing a time slice numbering of a microblog message according to a setting time granularity TG; step 4. using a theme emotion evolution model TSEM to continuously perform iterative updating on a variable (img file='dest_path_image002.TIF' wi='378' he='30' / ), (img file='dest_path_image004.TIF' wi='37' he='26' / ), (img file='dest_path_image006.TIF' wi='53' he='26' / ) and (img file='dest_path_image008.TIF' wi='39' he='30' / ); and step 5. judging the theme attribution of a microblog (i)m( / i) that is published in the time slice (i)d( / i) by (img file='897717dest_path_image008.TIF' wi='39' he='30' / ). According to the invention, the method can effectively find the theme emotion evolution model that is hidden in the microblog message.

Description

Technical field [0001] The invention relates to the technical field of network public opinion analysis, in particular to a subject emotion evolution analysis method applied to microblog messages in a Web2.0 environment. Background technique [0002] Weibo is an integrated and open Internet social service that emerged in the Web2.0 era. It allows users to publish short text messages to the public. Due to its simple features, it is increasingly favored by Internet users. Currently, Sina Weibo has more than 300 million users, and a large number of Weibo messages are released every day. Among these massive microblog messages, there are many resources full of personal emotions. How to efficiently and automatically extract topics and emotions from these microblog messages, and perform evolutionary analysis on themes and emotions, is a hot topic with great research value. [0003] The algorithms of online text emotion mining can be roughly classified into three categories: supervised em...

Claims

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Application Information

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Patent Type & Authority Patents(China)
IPC IPC(8): G06F17/27G06F17/30
Inventor 黄发良李超雄李璇元昌安
Owner FUJIAN NORMAL UNIV
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