Code and models to accompany the paper:
Marcus Astrup Hansen and Daniel Hershcovich. A Dataset of Sustainable Diet Arguments on Twitter. In Proceedings of the 2022 Workshop on NLP for Positive Impact, December 2022.
@inproceedings{hansen-hershcovich-2022-dataset,
title = "A Dataset of Sustainable Diet Arguments on {T}witter",
author = "Hansen, Marcus and
Hershcovich, Daniel",
booktitle = "Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)",
month = dec,
year = "2022",
address = "Abu Dhabi, United Arab Emirates (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.nlp4pi-1.5",
pages = "40--58",
abstract = "Sustainable development requires a significant change in our dietary habits. Argument mining can help achieve this goal by both affecting and helping understand people{'}s behavior. We design an annotation scheme for argument mining from online discourse around sustainable diets, including novel evidence types specific to this domain. Using Twitter as a source, we crowdsource a dataset of 597 tweets annotated in relation to 5 topics. We benchmark a variety of NLP models on this dataset, demonstrating strong performance in some sub-tasks, while highlighting remaining challenges.",
}