Abstract
This paper describes our approach to the Emotion Intensity shared task. A parallel architecture of Convolutional Neural Network (CNN) and Long short term memory networks (LSTM) alongwith two sets of features are extracted which aid the network in judging emotion intensity. Experiments on different models and various features sets are described and analysis on results has also been presented.
Cite
CITATION STYLE
Meisheri, H., Saha, R., Sinha, P., & Dey, L. (2017). Textmining at EmoInt-2017: A deep learning approach to sentiment intensity scoring of English tweets. In EMNLP 2017 - 8th Workshop on Computational Approaches to Subjectivity, Sentiment and Social Media Analysis, WASSA 2017 - Proceedings of the Workshop (pp. 193–199). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w17-5226
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