Online news and information sources are convenient and accessible ways to learn about current issues. For instance, more than 300 million people engage with posts on Twitter globally, which provides the possibility to disseminate misleading information. There are numerous cases where violent crimes have been committed due to fake news. This research presents the CovidMis20 dataset (COVID-19 Misinformation 2020 dataset), which consists of 1,375,592 tweets collected from February to July 2020. CovidMis20 can be automatically updated to fetch the latest news and is publicly available at: https://github.com/everythingguy/CovidMis20. This research was conducted using Bi-LSTM deep learning and an ensemble CNN+Bi-GRU for fake news detection. The results showed that, with testing accuracy of 92.23% and 90.56%, respectively, the ensemble CNN+Bi-GRU model consistently provided higher accuracy than the Bi-LSTM model.
翻译:在线新闻和信息来源是了解当前问题的方便和便捷的途径。例如,3亿多人在全球Twitter上发表文章,这为传播误导信息提供了可能性。有许多案件因假新闻而犯下暴力罪行。这项研究展示了CovidMIs20数据集(COVID-19错误信息2020数据集),该数据集包括从2020年2月至7月收集的1 375 592个推特。CovidMIs20可以自动更新以获取最新消息,并公布在以下网址上:https://github.com/Severytingguy/CovidMis20。这项研究是利用Bi-LSTM深层学习和全套CNN+BI-GRU进行,以进行假新闻探测。结果显示,在测试精度分别为92.23%和90.56%的情况下,全能CNN+Bi-GRU模型一直提供比Bi-LSTM模型更高的精度。