INGEOTEC at SemEval-2024 Task 10: Bag of Words Classifiers

Daniela Moctezuma, Eric Tellez, Jose Ortiz Bejar, Mireya Paredes


Abstract
The Emotion Recognition in Conversation subtask aims to predict the emotions of the utterance of a conversation. In its most basic form, one can treat each utterance separately without considering that it is part of a conversation. Using this simplification, one can use any text classification algorithm to tackle this problem. This contribution follows this approach by solving the problem with different text classifiers based on Bag of Words. Nonetheless, the best approach takes advantage of the dynamics of the conversation; however, this algorithm is not statistically different than a Bag of Words with a Linear Support Vector Machine.
Anthology ID:
2024.semeval-1.162
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:
1115–1120
Language:
URL:
https://aclanthology.org/2024.semeval-1.162
DOI:
10.18653/v1/2024.semeval-1.162
Bibkey:
Cite (ACL):
Daniela Moctezuma, Eric Tellez, Jose Ortiz Bejar, and Mireya Paredes. 2024. INGEOTEC at SemEval-2024 Task 10: Bag of Words Classifiers. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 1115–1120, Mexico City, Mexico. Association for Computational Linguistics.
Cite (Informal):
INGEOTEC at SemEval-2024 Task 10: Bag of Words Classifiers (Moctezuma et al., SemEval 2024)
Copy Citation:
PDF:
https://preview.aclanthology.org/nschneid-patch-4/2024.semeval-1.162.pdf
Supplementary material:
 2024.semeval-1.162.SupplementaryMaterial.txt