Document emotion analysis method and apparatus, electronic device and readable storage medium

Abstract

Embodiments of the invention provide a document emotion analysis method and apparatus, an electronic device and a readable storage medium. The document emotion analysis method and apparatus can assistin improving an analysis effect, and enables emotion analysis to be closer to daily life. The method comprises the steps of obtaining a document, and preprocessing the document to obtain clauses andwords of the document; establishing index relationships between the clauses and the document, and between the words and the document; modeling the clauses and the words by utilizing a subject emotionmodel, generating emotions of the clauses and themes of the words in the document, and establishing corresponding relationships between the clauses and the words; according to the emotions of the clauses, the themes of the words, the corresponding relationships between the clauses and the words, and the index relationships between the clauses and the document, and between the words and the document, calculating probability distribution of "document-emotion-clause" and probability distribution of "document-theme-word"; and according to the probability distribution of "document-emotion-clause" and the probability distribution of "document-theme-word", calculating an emotional tendency of the document.

Description

technical field [0001] The present invention relates to the technical field of the Internet, in particular to a method, device, electronic equipment and readable storage medium for document sentiment analysis. Background technique [0002] With the rapid development of Internet technology, various Internet applications such as new media and e-commerce have been popularized, such as social networks, Weibo, WeChat, e-commerce, etc. Information in these fields is increasingly affecting all aspects of people's lives. Taking the field of e-commerce as an example, consumers' shopping habits have quietly shifted from offline to online. The popularity of online shopping has brought about an explosion of product review information, which has become an indispensable part of e-commerce. component. By analyzing the dissemination information of social networks, comments on Weibo and WeChat, and document information such as commodity review information in the e-commerce field, it is easi...

AI Technical Summary

Problems solved by technology

[0006] (1) The determination of emotional feature words depends on specific field information, and the adaptability of the algorithm is poor

[0007] (2) The granularity of sentiment analysis is relatively large, and the basic object of analysis is the whole sentence or even the whole document. In real life, a document may have multiple sentiment tendencies

[0008] (3) It is necessary to manually label the information, which will consume a lot of labor costs

Moreover, due to the different cognitive levels of different annotators, the annotation results may also be different

[0009] (4) There is a lack of feedback mechanism, and the existing technology lacks the relearning of wrong judgment results, or the process of re-enriching the unsampled lexicon

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