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