Case microblog comment emotion classification method fusing emotion knowledge
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
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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 bus crash 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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