Orientation analysis for Chinese blog text based on semantic comprehension

doi:10.3724/SP.J.1087.2011.02130

Journal of Computer Applications ›› 2011, Vol. 31 ›› Issue (08): 2130-2133.DOI: 10.3724/SP.J.1087.2011.02130

• Artificial intelligence • Previous Articles Next Articles

Orientation analysis for Chinese blog text based on semantic comprehension

Feng-ying HE

College of Mathematics and Computer Science, Fuzhou University, Fuzhou Fujian 350002, China

Received:2011-02-15 Revised:2011-04-14 Online:2011-08-01 Published:2011-08-01
Contact: Feng-ying HE

基于语义理解的中文博文倾向性分析

何凤英

福州大学数学与计算机科学学院，福州350002

通讯作者: 何凤英
作者简介:何凤英(1979-)，女，福建武平人，讲师，硕士，主要研究方向：数据网格、分布计算。
基金资助:
福建省教育厅科研资助项目(JB09003)

Abstract

Abstract: Blog has been accepted by more and more people as a popular information and cultural carrier. Orientation analysis for blog text also has become a hot spot in the field of information mining. The previous researches of text orientation mainly focus on plain text or news comments. A method of orientation analysis for blog text based on semantic comprehension was proposed according to the characteristics of blog text. Firstly, a Chinese basic emotional lexicon dictionary based on the HowNet emotional word set was constructed and the emotional value of Chinese emotional words was calculated on the basis of the similarity of Chinese words. Then, the adverbs and its influence on identification of text orientation in the semantic level were analyzed. Finally, the results were amended by using bloggers' language style factors and then the sentimental classification for blog text was realized. The experimental results show that the proposed method can effectively judge the blog text sentimental preference.

Key words: orientation analysis, semantic comprehension, sentiment lexicon, blogger language style, adverb

摘要： 博客作为一种大众化的信息及文化载体被越来越多的人所接受，博客文本的情感倾向性分析也逐渐成为信息挖掘领域的热点。目前，文本倾向性分析的研究大都围绕普通文本、新闻评论进行，针对博客文本的特点，提出一种基于语义理解的博客文本倾向性分类方法。首先以HowNet情感词语集为基准，构建中文基础情感词典，并用中文词语相似度方法计算词语的情感权值，同时分析语义层副词的出现规律及其对文本倾向性判断的影响，最后利用博主的语言风格因素对倾向性结果进行修正实现博文的情感分类。实验表明，该方法能有效地判定博客文本情感倾向性。

关键词: 倾向性分析, 语义理解, 情感词典, 博主语言风格, 副词

CLC Number:

TP391.1

Feng-ying HE. Orientation analysis for Chinese blog text based on semantic comprehension[J]. Journal of Computer Applications, 2011, 31(08): 2130-2133.

何凤英. 基于语义理解的中文博文倾向性分析[J]. 计算机应用, 2011, 31(08): 2130-2133.

References

[1] China Internet Network Information Center. The 23th statistical report of China Internet network development [EB /OL]. [2011-01-10]. http://www.cnnic.net.cn/uploadfiles/pdf/2009/1/13/92458.pdf.

[2] 朱嫣岚,闵锦,周雅倩,等.基于HowNet的词汇语义倾向计算[J].中文信息学报,2006,20(1):14-20.

[3] YI J, NASUKAWA T, BUNESCU R, et al. Sentiment analyzer: Extracting sentiments about a given topic using natural language processing techniques [C]// Proceedings of the 3rd IEEE International Conference on Data Mining. Washington, DC: IEEE Computer Society, 2003: 427-434.

[4] 刘永丹,曾海泉,李荣陆,等.基于语义分析的倾向性文本过滤[J].通信学报,2004,25(7):78-85.

[5] PANG B, LEE L, VAITHYANATHAN S. Thumbs up? Sentiment classification using machine learning techniques [C]// Proceedings of the Conference on Empirical Methods in Natural Language Processing. Stroudsburg: Association for Computational Linguistics, 2002: 79-86.

[6] 徐琳宏,林鸿飞,杨志豪.基于语义理解的文本倾向性识别机制[J].中文信息学报,2007,21(1):96-100.

[7] TURNEY P D, LITTMAN M L. Measuring praise and criticism: Inference of semantic orientation from association [J]. ACM Transactions on Information Systems, 2003, 21(4): 315-346.

[8] 柳位平,朱艳辉,栗春亮,等.中文基础情感词词典构建方法研究[J].计算机应用,2009,29(10):2875-2877.

[9] ESULI A, SEBASTIANI F. Sentiwordnet: A publicly available lexical resource for opinion mining [C]// Proceedings of LREC-06, the 5th Conference on Language Resources and Evaluation. Genova, Italy: [s.n.], 2006: 417-422.

[10] 姚天昉,娄德成.汉语情感词语义倾向判别的研究[C]//ICCC2007:第七届中文信息处理国际会议论文集.北京：电子工业出版社，2007：221-225.

[11] HATZIVASSILOGLOU V, MCKEOWN K. Predicting the semantic orientation of adjectives [C]// ACL-97: Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics. Madrid, Spain: [s.n.], 1997:174-181.

[12] TURNEY P. Thumbs up or thumbs down? Semantic orientation applied to unsupervised classification of reviews [C]// ACL-02: Proceedings of the 40th Annual Meeting of the Association for Computational Linguistics. Philadelphia, PA: [s.n.], 2002: 417-424.

[13] 蔺璜,郭姝慧.程度副词的特点范围与分类[J].山西大学学报：哲学社会科学版,2003,26(2):71-74.

[14] 林炜,林世平.中文倾向性挖掘中情感词修饰极性的研究[J].计算机科学,2008,35(8):208-210.

[15] 廖祥文.基于博主背景的博客倾向性检索归一化策略[J].中文信息学报,2010,24(3):75-80.

[16] 应伟,王正欧,安金龙.一种基于改进的支持向量机的多类文本分类方法[J].计算机工程,2006,32(16):74-76.

Orientation analysis for Chinese blog text based on semantic comprehension

基于语义理解的中文博文倾向性分析

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