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Affective computing method for microblog emotion icon based on point mutual information

An emoji and point-to-point mutual information technology, applied in computing, other database retrieval, network data retrieval, etc., can solve the problems of inability to conduct comprehensive comparison, and the emotional value of emoji is not standardized, so as to facilitate comprehensive comparison and later use, Accurate results

Inactive Publication Date: 2017-03-15
SHANGHAI UNIV
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  • Summary
  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0008] (3) The emotional value of the finally obtained emoticons is not standardized, and comprehensive comparison cannot be made

Method used

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  • Affective computing method for microblog emotion icon based on point mutual information
  • Affective computing method for microblog emotion icon based on point mutual information
  • Affective computing method for microblog emotion icon based on point mutual information

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Embodiment

[0049] In this embodiment, about 5 million pieces of Weibo data are crawled from the Sina Weibo website as a basic corpus.

[0050] A microblog emoji emotion calculation method based on point mutual information, its steps are as follows:

[0051] S1. Crawl about 5 million Weibo data from the Sina Weibo website as the basic corpus, filter the Weibo data in the corpus, and keep only Weibo that contains both emoji and emotional words, such as "[哈哈][哈哈 ] This mascot is so cute!" After filtering, there are about 520,000 Weibo posts left;

[0052] S2. Perform pre-operations such as word segmentation and stop word filtering for each Weibo, and perform combined operations on emotional words preceded by negative words and degree words and calculate their emotional value. For example, on Weibo, "[哈哈][哈哈] This mascot is so cute!" After processing, it becomes "[哈哈][哈哈] The mascot is so cute", and the emotional value of the combined emotional word "So cute" is 1.8*5 =9.0;

[0053] S3. Extract the...

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Abstract

The invention discloses an affective computing method for a microblog emotion icon based on point mutual information. The method comprises the following steps: (1) extracting large-scale Sina microblogs and filtering and only remaining the microblogs including emotion icons and emotion words; (2) pre-processing the microblogs, combining the emotion words front connected with negative words and degree words and calculating emotion values thereof; (3) extracting 'emotion icon-emotion word' co-occurrence pairs from the pre-processed microblogs and forming a co-occurrence pair set; (4) calculating point mutual information of the emotion icons in the 'emotion icon-emotion word' co-occurrence pair set and each co-occurrence emotion word; (5) calculating an initial emotion value of each emotion icon; and (6) standardizing the initial emotion value of the emotion icon. According to the method, the point mutual information of the co-occurrence emotion word and the emotion icon is utilized to calculate and standardize the emotion values of the emotion icons; the method is simple and direct; the result is accurate.

Description

Technical field [0001] The invention relates to an emotion calculation method for microblog emoticons, in particular to a microblog emoticon emotion calculation method based on point mutual information. Background technique [0002] With the rapid development of Internet technology, Weibo, as a new type of information dissemination carrier, has quickly integrated into people's lives. People log on to the Weibo platform through various terminals and publish information including text, pictures, videos, emoticons, etc. to express their thoughts and emotions. Emoticons are concise and vivid, and can intuitively reflect emotions through various expressions and actions. Therefore, people are increasingly interspersing emojis in Weibo texts to express emotions. [0003] At present, the mainstream way of sentiment analysis of Weibo still only focuses on text information and ignores emoticons. There are two main ideas: methods based on emotional knowledge and methods based on machine lear...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30G06Q50/00
CPCG06F16/951G06Q50/01
Inventor 陈雪郭峻材
Owner SHANGHAI UNIV
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