A Comparative Analysis of Sentiment Analysis and Emotion Detection Problems on Texts
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Publisher
Springer Nature Singapore
Link
https://link.springer.com/content/pdf/10.1007/978-981-19-7524-0_41
Reference9 articles.
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2. ISEAR dataset. https://www.unige.ch/cisa/
3. Nandwani, P., Verma, R.: A review on sentiment analysis and emotion detection from text. Soc. Netw. Anal. Min. 11, 81 (2021). https://doi.org/10.1007/s13278-021-00776-6
4. Asghar, M.Z., Subhan, F., Imran, M., et al.: Performance evaluation of supervised machine learning techniques for efficient detection of emotions from online content (2019). Preprints.org. https://doi.org/10.20944/preprints201908.0019.v1
5. Gao, W., Li, S., Lee, S.Y.M., Zhou, G., Huang, C.-R.: Joint learning on sentiment and emotion classification. In: Proceedings of the 22nd ACM international conference on Information and Knowledge Management (CIKM ’13). Association for Computing Machinery, New York, NY, USA, pp. 1505–1508 (2013). https://doi.org/10.1145/2505515.2507830
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