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Cross-domain and cross-category news commentary emotion prediction method

A prediction method, a cross-domain technology, applied in the field of online news comment sentiment prediction

Inactive Publication Date: 2014-12-24
NANKAI UNIV
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  • Abstract
  • Description
  • Claims
  • Application Information

AI Technical Summary

Problems solved by technology

[0007] The purpose of the present invention is to solve the news comment sentiment prediction problem in two related but different fields with different emotional categories, and propose a cross-domain and cross-category news comment sentiment prediction method

Method used

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  • Cross-domain and cross-category news commentary emotion prediction method
  • Cross-domain and cross-category news commentary emotion prediction method
  • Cross-domain and cross-category news commentary emotion prediction method

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Embodiment Construction

[0083] Prepare news comment datasets in two fields, such as comments on 5,174 social channels of Sina News website and 5,431 hot news on Entertainment Channel of Tencent News website from January 2011 to June 2011. The comments of the two datasets are marked with emotions For statistical information on categories and sentimental tendencies, see image 3 and Figure 4 . For news comment datasets in the social and entertainment fields, experts are invited to label each comment in the dataset with emotional category labels and emotional orientation labels. The predefined emotional categories are consistent with the user sentiment voting services provided by the corresponding news websites The emotional categories are the same, and the emotional tendencies are divided into positive and negative categories. The social domain is used as the source domain, and the entertainment domain is used as the target domain; the source domain uses 8 types of emotional categories (touched, sym...

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Abstract

The invention provides a cross-domain and cross-category news commentary emotion prediction method. According to the method disclosed by the invention, under the condition that a target domain is provided with a small amount of annotation data only and another related but different source domain is provided with a large amount of annotation data, knowledge transfer among different domains is realized through simulating the relationship between the emotion category collections of the source domain and the target domain, and a cross-domain and cross-category news commentary emotion prediction model is built, so that the problem of difficulty in emotion prediction of news commentaries of the target domain is solved; under the situation that the emotion category collections of the source domain and the target domain are different, the method disclosed by the invention is significantly better than other alternative cross-domain and cross-category online news commentary emotion prediction methods, and high cost resulting from manual annotation work and energy consumed through training more classification models are greatly reduced. The method can be applied to user sentiment analysis and public sentiment supervision.

Description

technical field [0001] The invention belongs to the field of web information retrieval and mining, and specifically relates to a method for predicting online news comment sentiment from various information sources such as heterogeneous news content, comment content, and user emotion. Background technique [0002] In recent years, with the rapid development of information retrieval, machine learning, and natural language processing, text mining and sentiment analysis have attracted extensive attention from researchers. Sentiment classification methods based on supervised learning have emerged one after another and become a research hotspot in sentiment analysis. How to establish a multi-domain news comment sentiment prediction method and use the knowledge of one domain to help the learning of classification models in other domains is an urgent problem to be solved. Hereinafter, the emotion classification problem of multi-type emotion division is called "emotion classificatio...

Claims

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Application Information

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Patent Type & Authority Applications(China)
IPC IPC(8): G06F17/30
CPCG06F16/9535Y02D10/00
Inventor 张莹赵雪乜鹏俞力袁晓洁
Owner NANKAI UNIV
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