Abstract
In this system paper for SemEval-2024 Task3 subtask 2, I present my simple textual approach to emotion classification and emotioncause analysis in conversations using machinelearning and next sentence prediction. I train aSpaCy model for emotion classification and usenext sentence prediction with BERT for emotion cause analysis. While speaker names andaudio-visual clips are given in addition to textof the conversations, my approach uses textualdata only to test my methodology to combinemachine learning with next sentence prediction.This paper reveals both strengths and weaknesses of my trial, suggesting a direction offuture studies to improve my introductory solution.- Anthology ID:
- 2024.semeval-1.55
- 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:
- 361–364
- Language:
- URL:
- https://aclanthology.org/2024.semeval-1.55
- DOI:
- Cite (ACL):
- Hidetsune Takahashi. 2024. Hidetsune at SemEval-2024 Task 3: A Simple Textual Approach to Emotion Classification and Emotion Cause Analysis in Conversations Using Machine Learning and Next Sentence Prediction. In Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024), pages 361–364, Mexico City, Mexico. Association for Computational Linguistics.
- Cite (Informal):
- Hidetsune at SemEval-2024 Task 3: A Simple Textual Approach to Emotion Classification and Emotion Cause Analysis in Conversations Using Machine Learning and Next Sentence Prediction (Takahashi, SemEval 2024)
- PDF:
- https://preview.aclanthology.org/jeptaln-2024-ingestion/2024.semeval-1.55.pdf