Industry comment data fine grain sentiment analysis method

Abstract

The invention relates to an industry comment data fine grain sentiment analysis method. The industry comment data fine grain sentiment analysis method is applied to Internet data analysis and comprises obtaining comment data of e-commerce industry goods and preprocessing the comment data; establishing initial industry sentiment word libraries and computing distribution of words under different sentiment polarities through 1-gram and 2-gram; performing Chinese word segmentation on the comment data; based on the sentiment word libraries established through the 1-gram and the 2-gram, utilizing combined sentiment models to perform word modeling to obtain the probability distribution of the words which belong to different topics under different sentiment distributions; utilizing context information to re-determine the sentiment alignment of sentiment words in sentences; performing named entity identification and extracting comment characteristics through conditional random fields to compute the sentiment alignment of comment words of the comment characteristics. The industry comment data fine grain sentiment analysis method computes the sentiment of the comment words through the two dimensions of topic and sentiment to achieve fine grain sentiment analysis on the industry comment data, thereby achieving high precision and interpretability of analysis results.

Description

technical field [0001] The invention belongs to the field of Internet data analysis, and relates to a sentiment analysis technology of comment data, in particular to a method for fine-grained sentiment analysis of industry comment data. Background technique [0002] With the advent of the era of big data, more and more information appears in the form of crowdsourcing through the collective wisdom of netizens, and more and more people like to exchange their opinions online, so a large number of information including Tendency review information, such as Douban movie reviews, book reviews, and product reviews on e-commerce websites. Merchants hope to obtain the emotional tendencies contained in these electronic information through information processing methods, so as to obtain consumer feedback and modify market decisions. For example, before purchasing an electronic product, people hope to know other people's evaluation of the product, what are the advantages and disadvantag...

AI Technical Summary

Problems solved by technology

[0005] The present invention aims at the problem that the analysis result of the existing non-supervised model is poor, the field is highly pertinent, and the sentiment analysis result used is rough, and proposes a fine-grained sentiment analysis method of industry comment data combined with an unsupervised sentiment vocabulary, aiming at Realize the analysis of the emotional tendency of ordinary users towards the research objects with a relatively high degree of interpretability and accuracy

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