Abstract
Current research on emotion detection focuses on the recognizing explicit emotion expressions in text. In this paper, we propose an approach based on textual inference to detect implicit emotion expressions, that is, to capture emotion detection as an logical inference issue. The approach builds a natural logic system, in which emotional detection are decomposed into a series of logical inference process. The system also employ inference knowledge from textural inference resources for reasoning complex expressions in emotional texts. Experimental results show the efficiency in detecting implicit emotional expressions.
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Notes
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The mapping relation can be found in emotion lexicons, such as EmoLex.
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Acknowledgements
This work is supported by National Natural Science Foundation of China(61402341, 61402119) and Bidding Project of GDUFS Laboratory of Language Engineering and Computing(LEC2016ZBKT001, LEC2016ZBKT002).
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Ren, H., Ren, Y., Li, X., Feng, W., Liu, M. (2017). Natural Logic Inference for Emotion Detection. In: Sun, M., Wang, X., Chang, B., Xiong, D. (eds) Chinese Computational Linguistics and Natural Language Processing Based on Naturally Annotated Big Data. NLP-NABD CCL 2017 2017. Lecture Notes in Computer Science(), vol 10565. Springer, Cham. https://doi.org/10.1007/978-3-319-69005-6_35
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