Abstract
The key problem to be solved in the analysis of micro-blog emotion is the micro-blog sentiment polarity classification. Based on the analysis of various factors affecting sentiment classification of micro-blog, we recognize word sentimental polarity, extract affective and weighted sentimental feature in the sentence level. Then support vector machine (SVM) classifier is used for emotion recognition and micro-blog classification. Finally, we perform the classification model with the micro-blog corpus data sets, and improve classification accuracy by calculating confidence. The experimental results verify the effectiveness of the micro-blog sentiment polarity classification model applied to the micro-blog.
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Chen, P., Fu, X., Teng, S., Lin, S., Lu, J. (2015). Research on Micro-blog Sentiment Polarity Classification Based on SVM. In: Zu, Q., Hu, B., Gu, N., Seng, S. (eds) Human Centered Computing. HCC 2014. Lecture Notes in Computer Science(), vol 8944. Springer, Cham. https://doi.org/10.1007/978-3-319-15554-8_32
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DOI: https://doi.org/10.1007/978-3-319-15554-8_32
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