论文标题
checkthat的qmul-sd！ 2020：使用增强的CT-Bert确定COVID-19-19
QMUL-SDS at CheckThat! 2020: Determining COVID-19 Tweet Check-Worthiness Using an Enhanced CT-BERT with Numeric Expressions
论文作者
论文摘要
本文介绍了QMUL-SDS团队参与2020 CEACKTHAT的任务1！共享任务。此任务的目的是确定有关Covid-19的推文的访问性，以识别和优先考虑需要事实检查的推文。总体目的是进一步支持持续的努力，以保护公众免受虚假新闻的影响，并帮助人们找到可靠的信息。我们描述和分析提交的结果。我们表明，使用数字表达式增强的COVID-TWITTER-BERT（CT-BERT）的CNN可以有效地从基线结果中提高性能。我们还展示了培训数据增强的结果，以及有关其他主题的谣言。我们最好的系统在任务中排名第四，令人鼓舞的结果在未来取得了改善的可能性。
This paper describes the participation of the QMUL-SDS team for Task 1 of the CLEF 2020 CheckThat! shared task. The purpose of this task is to determine the check-worthiness of tweets about COVID-19 to identify and prioritise tweets that need fact-checking. The overarching aim is to further support ongoing efforts to protect the public from fake news and help people find reliable information. We describe and analyse the results of our submissions. We show that a CNN using COVID-Twitter-BERT (CT-BERT) enhanced with numeric expressions can effectively boost performance from baseline results. We also show results of training data augmentation with rumours on other topics. Our best system ranked fourth in the task with encouraging outcomes showing potential for improved results in the future.
