Abstract
Sentiment analysis of Chinese microblogs is important for scientific research in public opinion supervision, personalized recommendation and social computing. By studying the evaluation task of NLP&CC’2012, we mainly implement two tasks, namely the extraction of opinion sentence and the determination of sentiment orientation for microblogs. First, we manually label the sample of microblog corpus supplied by the organization, and expand the sentiment lexicon by introducing the Internet sentiment words; second, we construct the different feature sets based on the analysis of the characteristic of Chinese microblogs. Finally, we use SVM classifier to generate a model based on training corpus, and implement the predication of test corpus. Evaluation results show our work has good performance on two tasks.
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Shi, H., Chen, W., Li, X. (2013). Opinion Sentence Extraction and Sentiment Analysis for Chinese Microblogs. In: Zhou, G., Li, J., Zhao, D., Feng, Y. (eds) Natural Language Processing and Chinese Computing. NLPCC 2013. Communications in Computer and Information Science, vol 400. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-41644-6_41
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DOI: https://doi.org/10.1007/978-3-642-41644-6_41
Publisher Name: Springer, Berlin, Heidelberg
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