Abstract
Millions of users share their opinions in microblog every day, which makes sentiment analysis in microblog an important and practical issue in social networks. In this paper, the problem of public sentiment analysis, and the construction of emoticon networks model are solved using emoticons. Based on large-scale corpus, FP-growth algorithm combined with the semantic similarity is proposed to aggregate similar emoticons. The construction of emoticon networks model is based on Pointwise Mutual Information. And a microblog orientation analysis framework for both emoticon messages and non-emoticon messages is presented. Experimental results have shown that our approach works effectively for microblog sentiment analysis.
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Pei, S., Zhang, L., Li, A. (2014). Microblog Sentiment Analysis Model Based on Emoticons. In: Han, W., Huang, Z., Hu, C., Zhang, H., Guo, L. (eds) Web Technologies and Applications. APWeb 2014. Lecture Notes in Computer Science, vol 8710. Springer, Cham. https://doi.org/10.1007/978-3-319-11119-3_12
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DOI: https://doi.org/10.1007/978-3-319-11119-3_12
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