arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 2004.08789cs.CL
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BanFakeNews: A Dataset for Detecting Fake News in Bangla

Shahjalal University of Science and Technology(沙赫贾拉尔科技大学);University of Houston(休斯顿大学)

Md Zobaer Hossain, Md Ashraful Rahman, Md Saiful Islam, Sudipta Kar

英文摘要:

Observing the damages that can be done by the rapid propagation of fake news in various sectors like politics and finance, automatic identification of fake news using linguistic analysis has drawn the attention of the research community. However, such methods are largely being developed for English where low resource languages remain out of the focus. But the risks spawned by fake and manipulative news are not confined by languages. In this work, we propose an annotated dataset of ~50K news that can be used for building automated fake news detection systems for a low resource language like Bangla. Additionally, we provide an analysis of the dataset and develop a benchmark system with state of the art NLP techniques to identify Bangla fake news. To create this system, we explore traditional linguistic features and neural network based methods. We expect this dataset will be a valuable resource for building technologies to prevent the spreading of fake news and contribute in research with low resource languages.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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