A Dataset of Sustainable Diet Arguments on Twitter

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Standard

A Dataset of Sustainable Diet Arguments on Twitter. / Hansen, Marcus Astrup ; Hershcovich, Daniel.

Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics, 2022. p. 40–58.

Research output: Chapter in Book/Report/Conference proceeding › Article in proceedings › Research › peer-review

Harvard

Hansen, MA & Hershcovich, D 2022, A Dataset of Sustainable Diet Arguments on Twitter. in Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics, pp. 40–58, 2nd Workshop on NLP for Positive Impact (NLP4PI), Abu Dhab, United Arab Emirates, 07/12/2022. <https://aclanthology.org/2022.nlp4pi-1.5>

APA

Hansen, M. A., & Hershcovich, D. (2022). A Dataset of Sustainable Diet Arguments on Twitter. In Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI) (pp. 40–58). Association for Computational Linguistics. https://aclanthology.org/2022.nlp4pi-1.5

Vancouver

Hansen MA, Hershcovich D. A Dataset of Sustainable Diet Arguments on Twitter. In Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics. 2022. p. 40–58

Author

Hansen, Marcus Astrup ; Hershcovich, Daniel. / A Dataset of Sustainable Diet Arguments on Twitter. Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI). Association for Computational Linguistics, 2022. pp. 40–58

Bibtex

@inproceedings{edff766380c943f4a7b75a623284e563,
title = "A Dataset of Sustainable Diet Arguments on Twitter",
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{\textquoteright}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.",
author = "Hansen, {Marcus Astrup} and Daniel Hershcovich",
year = "2022",
language = "English",
pages = "40–58",
booktitle = "Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)",
publisher = "Association for Computational Linguistics",
note = "2nd Workshop on NLP for Positive Impact (NLP4PI) ; Conference date: 07-12-2022",

}

RIS

TY - GEN

T1 - A Dataset of Sustainable Diet Arguments on Twitter

AU - Hansen, Marcus Astrup

AU - Hershcovich, Daniel

PY - 2022

Y1 - 2022

N2 - 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.

AB - 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.

M3 - Article in proceedings

SP - 40

EP - 58

BT - Proceedings of the Second Workshop on NLP for Positive Impact (NLP4PI)

PB - Association for Computational Linguistics

T2 - 2nd Workshop on NLP for Positive Impact (NLP4PI)

Y2 - 7 December 2022

ER -

ID: 339843911