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Case microblog comment emotion classification method fusing emotion knowledge
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A microblog comment and classification method technology, applied in the field of natural language processing, can solve problems such as difficult to effectively use comment emoticons and low classification performance
Active Publication Date: 2020-06-23
KUNMING UNIV OF SCI & TECH
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[0004] The invention provides a case microblog comment emotion classification method that integrates emotional knowledge, which is used to solve the problem that the classification performance of the traditional method is not high in the case microblog comment emotion classification task, and it is difficult for the traditional sentiment analysis method to effectively use the common Emotional knowledge such as emoticons, negation rules, and new words for domain emotions
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Embodiment 1
[0032] Embodiment 1: as Figure 1-2 As shown, the emotional classification method of case Weibo comments integrated with emotional knowledge, the specific steps are as follows:
[0033] Step1. Build the case microblog comment corpus vocabulary: collect the case microblog comment text as the experimental data set, and perform data preprocessing for deleting meaningless characters, word segmentation, part-of-speech tagging text preprocessing, and obtain the case microblog comment corpus vocabulary;
[0034] Step2. Build a basic emotional dictionary: Based on the emotional vocabulary ontology of Dalian University of Technology, a total of 7 emotional categories such as joy, happiness, anger, sorrow, fear, evil, and shock were used to construct a basic emotional dictionary; by sorting out the existing emotional computing Resources, collect and classify commonly used emoticons and Internet buzzwords in Weibo, and obtain negative dictionary, degree adverb dictionary, emoticon collecti...
Embodiment 2
[0054] Embodiment 2: as Figure 1-2 As shown, the emotional classification method of case Weibo comments integrated with emotional knowledge, the specific steps are as follows:
[0055] Step 1. Collected comment data on Weibo of 7 cases that have attracted much attention in recent years from the Sina Weibo platform. Among them, the Laiyuan anti-murder case has a total of 10,812 sentences, the Jiangge case has a total of 13,624 sentences; the Zhao Yu bravery case has a total of 17,491 sentences; the Zhang Yingying murder case has a total of 17,875 sentences; the Chongqing buscrash case has a total of 33,774 sentences; 189,364 sentences; and 58,626 sentences in Xi'an Mercedes-Benz female car owner's rights protection case. Among them, these 189,364 comments will all be used as experimental data for the construction of the microblog emotion dictionary of the case; in addition, 30,000 comments were randomly sampled for manual labeling of emotions, and 11,593 sentences were final...
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Abstract
The invention relates to a case microblog comment emotion classification method fusing emotion knowledge, and belongs to the technical field of natural languageprocessing. According to the method, anemotion knowledge base containing a case microblog emotion dictionary, emoticons, network flow languages, a negative dictionary and a degree adverb dictionary is constructed; and constructing an attributive feature representation. Finally, semantic representation and attribute feature representation of comments are fused based on a convolutional neural network, an emotion classification model isconstructed, deep semantic features and serialized emotion knowledge features are extracted, and emotion classification is achieved. Experimental results based on case microblog comment corpora show that compared with a reference method INIT-CNN, the method has the advantage that two indexes of Macro _ F1 and Micro _ F1 are improved by 1.88% and 1.94% respectively.
Description
technical field [0001] The invention relates to a case microblog comment emotion classification method that integrates emotional knowledge, and belongs to the technical field of natural languageprocessing. Background technique [0002] Case public opinion refers to Internet public opinion related to the case. As a prominent representative of social media platforms, Weibo is an important source of public opinion on cases. Hot cases are often easily fermented and evolved rapidly on the Weibo platform, and generate massive comments and case public opinion. Public opinion on cases can easily lead to social turmoil and affect judicial decision-making. The country is also actively promoting the construction of smart courts. Therefore, the emotional classification of case microblog comments is very necessary and significant for timely understanding and mastering case public opinion so that relevant departments can make decisions quickly. [0003] The sentiment classification ta...
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