SSN_ARMM at SemEval-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using LinearSVC and TF-IDF

Rohith Arumugam, Angel Deborah, Rajalakshmi Sivanaiah, Milton R S, Mirnalinee Thankanadar


Abstract
Our paper explores a task involving the analysis of emotions and triggers within dialogues. We annotate each utterance with an emotion and identify triggers, focusing on binary labeling. We emphasize clear guidelines for replicability and conduct thorough analyses, including multiple system runs and experiments to highlight effective techniques. By simplifying the complexities and detailing clear methodologies, our study contributes to advancing emotion analysis and trigger identification within dialogue systems.
Anthology ID:
2024.semeval-1.105
Volume:
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
Month:
June
Year:
2024
Address:
Mexico City, Mexico
Editors:
Atul Kr. Ojha, A. Seza Doğruöz, Harish Tayyar Madabushi, Giovanni Da San Martino, Sara Rosenthal, Aiala Rosá
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
730–736
Language:
URL:
https://preview.aclanthology.org/build-pipeline-with-new-library/2024.semeval-1.105/
DOI:
10.18653/v1/2024.semeval-1.105
Bibkey:
Cite (ACL):
Rohith Arumugam, Angel Deborah, Rajalakshmi Sivanaiah, Milton R S, and Mirnalinee Thankanadar. 2024. SSN_ARMM at SemEval-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using LinearSVC and TF-IDF. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 730–736, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
SSN_ARMM at SemEval-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using LinearSVC and TF-IDF (Arumugam et al., SemEval 2024)
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PDF:
https://preview.aclanthology.org/build-pipeline-with-new-library/2024.semeval-1.105.pdf
Supplementarymaterial:
 2024.semeval-1.105.SupplementaryMaterial.txt
Supplementarymaterial:
 2024.semeval-1.105.SupplementaryMaterial.zip