Creation of Corpus and analysis in Code-Mixed Kannada-English Twitter data for Emotion Prediction

Abhinav Reddy Appidi, Vamshi Krishna Srirangam, Darsi Suhas, Manish Shrivastava


Abstract
Emotion prediction is a critical task in the field of Natural Language Processing (NLP). There has been a significant amount of work done in emotion prediction for resource-rich languages. There has been work done on code-mixed social media corpus but not on emotion prediction of Kannada-English code-mixed Twitter data. In this paper, we analyze the problem of emotion prediction on corpus obtained from code-mixed Kannada-English extracted from Twitter annotated with their respective ‘Emotion’ for each tweet. We experimented with machine learning prediction models using features like Character N-Grams, Word N-Grams, Repetitive characters, and others on SVM and LSTM on our corpus, which resulted in an accuracy of 30% and 32% respectively.
Anthology ID:
2020.coling-main.587
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Editors:
Donia Scott, Nuria Bel, Chengqing Zong
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
6703–6709
Language:
URL:
https://aclanthology.org/2020.coling-main.587
DOI:
10.18653/v1/2020.coling-main.587
Bibkey:
Cite (ACL):
Abhinav Reddy Appidi, Vamshi Krishna Srirangam, Darsi Suhas, and Manish Shrivastava. 2020. Creation of Corpus and analysis in Code-Mixed Kannada-English Twitter data for Emotion Prediction. In Proceedings of the 28th International Conference on Computational Linguistics, pages 6703–6709, Barcelona, Spain (Online). International Committee on Computational Linguistics.
Cite (Informal):
Creation of Corpus and analysis in Code-Mixed Kannada-English Twitter data for Emotion Prediction (Appidi et al., COLING 2020)
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PDF:
https://aclanthology.org/2020.coling-main.587.pdf