veranchos/arg_mining_tweets

该数据集包含与COVID-19相关的推文，用于SMM4H22 Task 2，即关于健康命令（如居家令、学校关闭和口罩令）的推文中的立场和前提分类。数据集包括训练和测试数据，以及未在官方SMM4H比赛中使用的关于疫苗命令的2070条注释推文和600条注释推文（这些推文的注释者间一致性较低）。

原始信息汇总

COVID-19相关推文的立场和前提分类数据集

数据集描述

该数据集用于SMM4H22任务2：关于健康指令（COVID-19）的推文立场和前提分类。

数据内容

• 训练和测试数据：
  • 训练数据：用于SMM4H 2022任务2的推文，标注了关于COVID-19指令（如居家令、学校关闭和口罩令）的立场和前提预测。
  • 测试数据：包含2070条关于疫苗指令的标注推文，这些推文未在官方SMM4H竞赛中使用。
  • 额外数据：包含600条关于疫苗指令的标注推文，这些推文因低注释者间一致性而未使用。

引用

如果您发现此数据集有用，请引用：

@inproceedings{davydova-tutubalina-2022-smm4h, title = "{SMM}4{H} 2022 Task 2: Dataset for stance and premise detection in tweets about health mandates related to {COVID}-19", author = "Davydova, Vera and Tutubalina, Elena", booktitle = "Proceedings of The Seventh Workshop on Social Media Mining for Health Applications, Workshop {&} Shared Task", month = oct, year = "2022", address = "Gyeongju, Republic of Korea", publisher = "Association for Computational Linguistics", url = "https://aclanthology.org/2022.smm4h-1.53", pages = "216--220", abstract = "This paper is an organizers{} report of the competition on argument mining systems dealing with English tweets about COVID-19 health mandates. This competition was held within the framework of the SMM4H 2022 shared tasks. During the competition, the participants were offered two subtasks: stance detection and premise classification. We present a manually annotated corpus containing 6,156 short posts from Twitter on three topics related to the COVID-19 pandemic: school closures, stay-at-home orders, and wearing masks. We hope the prepared dataset will support further research on argument mining in the health field.", }