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        <title>PCIC at SMM4H 2024: Enhancing Reddit Post Classification on Social Anxiety Using Transformer Models and Advanced Loss Functions</title>
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        <namePart type="given">Leon</namePart>
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    <abstract>We present our approach to solving the task of identifying the effect of outdoor activities on social anxiety based on reddit posts. We employed state-of-the-art transformer models enhanced with a combination of advanced loss functions. Data augmentation techniques were also used to address class imbalance within the training set. Our method achieved a macro-averaged F1-score of 0.655 on the test data, surpassing the workshop’s mean F1-Score of 0.519. These findings suggest that integrating weighted loss functions improves the performance of transformer models in classifying unbalanced text data, while data augmentation can improve the model’s ability to generalize.</abstract>
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%0 Conference Proceedings
%T PCIC at SMM4H 2024: Enhancing Reddit Post Classification on Social Anxiety Using Transformer Models and Advanced Loss Functions
%A Hecht, Leon
%A Pozos, Victor
%A Gomez Adorno, Helena
%A Fuentes-Pineda, Gibran
%A Sierra, Gerardo
%A Bel-Enguix, Gemma
%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 hecht-etal-2024-pcic
%X We present our approach to solving the task of identifying the effect of outdoor activities on social anxiety based on reddit posts. We employed state-of-the-art transformer models enhanced with a combination of advanced loss functions. Data augmentation techniques were also used to address class imbalance within the training set. Our method achieved a macro-averaged F1-score of 0.655 on the test data, surpassing the workshop’s mean F1-Score of 0.519. These findings suggest that integrating weighted loss functions improves the performance of transformer models in classifying unbalanced text data, while data augmentation can improve the model’s ability to generalize.
%U https://aclanthology.org/2024.smm4h-1.14
%P 63-66

Markdown (Informal)

[PCIC at SMM4H 2024: Enhancing Reddit Post Classification on Social Anxiety Using Transformer Models and Advanced Loss Functions](https://aclanthology.org/2024.smm4h-1.14) (Hecht et al., SMM4H-WS 2024)

• PCIC at SMM4H 2024: Enhancing Reddit Post Classification on Social Anxiety Using Transformer Models and Advanced Loss Functions (Hecht et al., SMM4H-WS 2024)

ACL

• Leon Hecht, Victor Pozos, Helena Gomez Adorno, Gibran Fuentes-Pineda, Gerardo Sierra, and Gemma Bel-Enguix. 2024. PCIC at SMM4H 2024: Enhancing Reddit Post Classification on Social Anxiety Using Transformer Models and Advanced Loss Functions. In Proceedings of The 9th Social Media Mining for Health Research and Applications (SMM4H 2024) Workshop and Shared Tasks, pages 63–66, Bangkok, Thailand. Association for Computational Linguistics.