@inproceedings{singhal-bedi-2024-transformers-smm4h,
title = "Transformers at {\#}{SMM}4{H} 2024: Identification of Tweets Reporting Children{'}s Medical Disorders And Effects of Outdoor Spaces on Social Anxiety Symptoms on {R}eddit Using {R}o{BERT}a",
author = "Singhal, Kriti and
Bedi, Jatin",
editor = "Xu, Dongfang and
Gonzalez-Hernandez, Graciela",
booktitle = "Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.smm4h-1.15",
pages = "67--70",
abstract = "With the widespread increase in the use of social media platforms such as Twitter, Instagram, and Reddit, people are sharing their views on various topics. They have become more vocal on these platforms about their views and opinions on the medical challenges they are facing. This data is a valuable asset of medical insights in the study and research of healthcare. This paper describes our adoption of transformer-based approaches for tasks 3 and 5. For both tasks, we fine-tuned large RoBERTa, a BERT-based architecture, and achieved a highest F1 score of 0.413 and 0.900 in tasks 3 and 5, respectively.",
}
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%0 Conference Proceedings
%T Transformers at #SMM4H 2024: Identification of Tweets Reporting Children’s Medical Disorders And Effects of Outdoor Spaces on Social Anxiety Symptoms on Reddit Using RoBERTa
%A Singhal, Kriti
%A Bedi, Jatin
%Y Xu, Dongfang
%Y Gonzalez-Hernandez, Graciela
%S Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F singhal-bedi-2024-transformers-smm4h
%X With the widespread increase in the use of social media platforms such as Twitter, Instagram, and Reddit, people are sharing their views on various topics. They have become more vocal on these platforms about their views and opinions on the medical challenges they are facing. This data is a valuable asset of medical insights in the study and research of healthcare. This paper describes our adoption of transformer-based approaches for tasks 3 and 5. For both tasks, we fine-tuned large RoBERTa, a BERT-based architecture, and achieved a highest F1 score of 0.413 and 0.900 in tasks 3 and 5, respectively.
%U https://aclanthology.org/2024.smm4h-1.15
%P 67-70
Markdown (Informal)
[Transformers at #SMM4H 2024: Identification of Tweets Reporting Children’s Medical Disorders And Effects of Outdoor Spaces on Social Anxiety Symptoms on Reddit Using RoBERTa](https://aclanthology.org/2024.smm4h-1.15) (Singhal & Bedi, SMM4H-WS 2024)
ACL