Abstract
Micro-blog emotion mining and emotion cause extraction are essential in social network data mining. This paper presents a novel approach on Chinese micro-blog emotion cause detection based on the ECOCC model, focusing on mining factors for eliciting some kinds of emotions. In order to do so, the corresponding emotion causes are extracted. Moreover, the proportions of different cause components under different emotions are also calculated by means of combining the emotional lexicon with multiple characteristics (e.g., emoticon, punctuation, etc.). Experimental results show the feasibility of the approach. The proposed approaches have important scientific values on social network knowledge discovery and data mining.
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Gao, K., Xu, H., Wang, J. (2015). Emotion Cause Detection for Chinese Micro-Blogs Based on ECOCC Model. In: Cao, T., Lim, EP., Zhou, ZH., Ho, TB., Cheung, D., Motoda, H. (eds) Advances in Knowledge Discovery and Data Mining. PAKDD 2015. Lecture Notes in Computer Science(), vol 9078. Springer, Cham. https://doi.org/10.1007/978-3-319-18032-8_1
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DOI: https://doi.org/10.1007/978-3-319-18032-8_1
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