Abstract
Nowadays, with the rapid development of social networks, community-oriented Web sentiment analysis technology has gradually become a hot topic in the field of data mining. Being concise and flexible, Chinese microblog poses new challenges for sentiment analysis. This paper proposes an approach to classify Chinese microblog sentiments into positive and negative by the plain Naive Bayes (NB) and Support Vector Machine (SVM). Based on data preprocessing, sentiment lexicon construction, combining element of users’ comments, this research posit this Comments-attached Microblog Sentiment Classification, which is a novel method of attaching microblog users’ comments to the target microblog in order to improve the accuracy of sentiment classification. The experiment proves the vitality of this method and the advancement of the indecency from the way of language expressions.
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Yan, B., Zhang, B., Su, H., Zheng, H. (2014). Comments-Attached Chinese Microblog Sentiment Classification Based on Machine Learning Technology. In: Huang, DS., Jo, KH., Wang, L. (eds) Intelligent Computing Methodologies. ICIC 2014. Lecture Notes in Computer Science(), vol 8589. Springer, Cham. https://doi.org/10.1007/978-3-319-09339-0_18
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DOI: https://doi.org/10.1007/978-3-319-09339-0_18
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