@inproceedings{arumugam-etal-2024-ssn,
title = "{SSN}{\_}{ARMM} at {S}em{E}val-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using {L}inear{SVC} and {TF}-{IDF}",
author = "Arumugam, Rohith and
Deborah, Angel and
Sivanaiah, Rajalakshmi and
R S, Milton and
Thankanadar, Mirnalinee",
editor = {Ojha, Atul Kr. and
Do{\u{g}}ru{\"o}z, A. Seza and
Tayyar Madabushi, Harish and
Da San Martino, Giovanni and
Rosenthal, Sara and
Ros{\'a}, Aiala},
booktitle = "Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)",
month = jun,
year = "2024",
address = "Mexico City, Mexico",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.semeval-1.105",
doi = "10.18653/v1/2024.semeval-1.105",
pages = "730--736",
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.",
}
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%0 Conference Proceedings
%T SSN_ARMM at SemEval-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using LinearSVC and TF-IDF
%A Arumugam, Rohith
%A Deborah, Angel
%A Sivanaiah, Rajalakshmi
%A R S, Milton
%A Thankanadar, Mirnalinee
%Y Ojha, Atul Kr.
%Y Doğruöz, A. Seza
%Y Tayyar Madabushi, Harish
%Y Da San Martino, Giovanni
%Y Rosenthal, Sara
%Y Rosá, Aiala
%S Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)
%D 2024
%8 June
%I Association for Computational Linguistics
%C Mexico City, Mexico
%F arumugam-etal-2024-ssn
%X 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.
%R 10.18653/v1/2024.semeval-1.105
%U https://aclanthology.org/2024.semeval-1.105
%U https://doi.org/10.18653/v1/2024.semeval-1.105
%P 730-736
Markdown (Informal)
[SSN_ARMM at SemEval-2024 Task 10: Emotion Detection in Multilingual Code-Mixed Conversations using LinearSVC and TF-IDF](https://aclanthology.org/2024.semeval-1.105) (Arumugam et al., SemEval 2024)
ACL