ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents
This paper describes our participation in Task 3 and Task 5 of the #SMM4H (Social Media Mining for Health) 2024 Workshop, explicitly targeting the classification challenges within tweet data. Task 3 is a multi-class classification task centered on tweets discussing the impact of outdoor environm...
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| Định dạng: | Conference paper |
| Ngôn ngữ: | English |
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2024
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| Truy cập trực tuyến: | https://scholar.dlu.edu.vn/handle/123456789/3554 https://aclanthology.org/2024.smm4h-1.1/ |
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oai:scholar.dlu.edu.vn:123456789-35542024-09-21T12:02:55Z ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents Tạ, Hoàng Thắng Abu Bakar Siddiqur Rahman Lotfollah Najjar Alexander Gelbukh Computer Science - Computation and Language; Computer Science - Computation and Language This paper describes our participation in Task 3 and Task 5 of the #SMM4H (Social Media Mining for Health) 2024 Workshop, explicitly targeting the classification challenges within tweet data. Task 3 is a multi-class classification task centered on tweets discussing the impact of outdoor environments on symptoms of social anxiety. Task 5 involves a binary classification task focusing on tweets reporting medical disorders in children. We applied transfer learning from pre-trained encoder-decoder models such as BART-base and T5-small to identify the labels of a set of given tweets. We also presented some data augmentation methods to see their impact on the model performance. Finally, the systems obtained the best F1 score of 0.627 in Task 3 and the best F1 score of 0.841 in Task 5. Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks 1-4 Khoa Công nghệ Thông tin 1 Tạ Hoàng Thắng Association for Computational Linguistics, ISBN 979-8-89176-150-6 2024-09-04T15:21:58Z 2024-09-04T15:21:58Z 2024-05-01 Conference paper Bài báo đăng trên KYHT quốc tế (có ISBN) https://scholar.dlu.edu.vn/handle/123456789/3554 https://aclanthology.org/2024.smm4h-1.1/ en Association for Computational Linguistics |
| institution |
Thư viện Trường Đại học Đà Lạt |
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Thư viện số |
| language |
English |
| topic |
Computer Science - Computation and Language; Computer Science - Computation and Language |
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Computer Science - Computation and Language; Computer Science - Computation and Language Tạ, Hoàng Thắng Abu Bakar Siddiqur Rahman Lotfollah Najjar Alexander Gelbukh ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| description |
This paper describes our participation in Task 3 and Task 5 of the #SMM4H
(Social Media Mining for Health) 2024 Workshop, explicitly targeting the
classification challenges within tweet data. Task 3 is a multi-class
classification task centered on tweets discussing the impact of outdoor
environments on symptoms of social anxiety. Task 5 involves a binary
classification task focusing on tweets reporting medical disorders in children.
We applied transfer learning from pre-trained encoder-decoder models such as
BART-base and T5-small to identify the labels of a set of given tweets. We also
presented some data augmentation methods to see their impact on the model
performance. Finally, the systems obtained the best F1 score of 0.627 in Task 3
and the best F1 score of 0.841 in Task 5. |
| format |
Conference paper |
| author |
Tạ, Hoàng Thắng Abu Bakar Siddiqur Rahman Lotfollah Najjar Alexander Gelbukh |
| author_facet |
Tạ, Hoàng Thắng Abu Bakar Siddiqur Rahman Lotfollah Najjar Alexander Gelbukh |
| author_sort |
Tạ, Hoàng Thắng |
| title |
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| title_short |
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| title_full |
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| title_fullStr |
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| title_full_unstemmed |
ThangDLU at #SMM4H 2024: Encoder-decoder models for classifying text data on social disorders in children and adolescents |
| title_sort |
thangdlu at #smm4h 2024: encoder-decoder models for classifying text data on social disorders in children and adolescents |
| publishDate |
2024 |
| url |
https://scholar.dlu.edu.vn/handle/123456789/3554 https://aclanthology.org/2024.smm4h-1.1/ |
| _version_ |
1813142631184596992 |