| 基于机器学习的网络新闻评论情感分类研究 |
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| 引用本文： | 周杰,林琛,李弼程.基于机器学习的网络新闻评论情感分类研究[J].计算机应用,2010,30(4):1011-1014. |
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| 作者姓名： | 周杰 林琛 李弼程 |
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| 作者单位： | 1. 信息工程大学信息工程学院2. |
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| 基金项目： | 国家863计划项目(2007AA01Z439) |
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| 摘 要： | 首先对网络新闻评论数据的特点进行归纳总结，选取不同的特征集、特征维度、权重计算方法和词性等因素进行分类测试，并对实验结果进行分析比较。对比结果表明：情感词和论据词语搭配效果优于仅使用情感词作为评论特征；另外该类数据中特征维度对分类准确率的影响减小,且TF-IDF权重计算方法仍优于布尔型权重；在词性选择上，名词和动词词性比形容词和副词取得更好的分类效果。
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| 关 键 词： | 网络新闻评论 中文信息处理 情感分类 机器学习 口语化评论 |
| 收稿时间： | 2009-09-08 |
| 修稿时间： | 2009-11-30 |
Research of sentiment classification for netnews comments by machine learning |
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| ZHOU Jie,LIN Chen,LI Bi-cheng.Research of sentiment classification for netnews comments by machine learning[J].journal of Computer Applications,2010,30(4):1011-1014. |
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| Authors: | ZHOU Jie LIN Chen LI Bi-cheng |
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| Affiliation: | Institute of Information Engineering/a>;Information Engineering University/a>;Zhengzhou Henan 450002/a>;China |
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| Abstract: | Netnews comments has become an important channel to express personal opinions for the common people,and sentiment analysis can find out the whole attitude of the common people for the news events.This paper summarized the characteristics of netnews comments firstly,and selected different sets of feature,different feature dimensions,different feature-weight methods and parts of speech to construct classifiers;then made the comparison and analysis to the experimental results.The results of comparison show tha... |
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| Keywords: | netnews comments Chinese information processing sentiment analysis machine learning oral comments |
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