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        <title>Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb Diet</title>
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    <abstract>Social media offers an accessible avenue for individuals of diverse backgrounds and circumstances to share their unique perspectives and experiences. Our study focuses on the experience of low carbohydrate diets, motivated by recent research and clinical trials that elucidates the diet’s promising health benefits. Given the lack of any suitable annotated dataset in this domain, we first define an annotation schema that reflects the interests of healthcare professionals and then manually annotate data from the Reddit social network. Finally, we benchmark the effectiveness of several classification approaches that are based on statistical Support Vector Machines (SVM) classifier, pre-train-then-finetune RoBERTa classifier, and, off-the-shelf ChatGPT API, on our annotated dataset. Our annotations and scripts that are used to download the Reddit posts are publicly available at https://data.csiro.au/collection/csiro:59208.</abstract>
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%0 Conference Proceedings
%T Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb Diet
%A Zou, Skyler
%A Dai, Xiang
%A Brinkworth, Grant
%A Taylor, Pennie
%A Karimi, Sarvnaz
%Y Demner-fushman, Dina
%Y Ananiadou, Sophia
%Y Cohen, Kevin
%S The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks
%D 2023
%8 July
%I Association for Computational Linguistics
%C Toronto, Canada
%F zou-etal-2023-social
%X Social media offers an accessible avenue for individuals of diverse backgrounds and circumstances to share their unique perspectives and experiences. Our study focuses on the experience of low carbohydrate diets, motivated by recent research and clinical trials that elucidates the diet’s promising health benefits. Given the lack of any suitable annotated dataset in this domain, we first define an annotation schema that reflects the interests of healthcare professionals and then manually annotate data from the Reddit social network. Finally, we benchmark the effectiveness of several classification approaches that are based on statistical Support Vector Machines (SVM) classifier, pre-train-then-finetune RoBERTa classifier, and, off-the-shelf ChatGPT API, on our annotated dataset. Our annotations and scripts that are used to download the Reddit posts are publicly available at https://data.csiro.au/collection/csiro:59208.
%R 10.18653/v1/2023.bionlp-1.38
%U https://aclanthology.org/2023.bionlp-1.38
%U https://doi.org/10.18653/v1/2023.bionlp-1.38
%P 406-412

Markdown (Informal)

[Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb Diet](https://aclanthology.org/2023.bionlp-1.38) (Zou et al., BioNLP 2023)

• Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb Diet (Zou et al., BioNLP 2023)

ACL

• Skyler Zou, Xiang Dai, Grant Brinkworth, Pennie Taylor, and Sarvnaz Karimi. 2023. Can Social Media Inform Dietary Approaches for Health Management? A Dataset and Benchmark for Low-Carb Diet. In The 22nd Workshop on Biomedical Natural Language Processing and BioNLP Shared Tasks, pages 406–412, Toronto, Canada. Association for Computational Linguistics.