BanFakeNews: A Dataset for Detecting Fake News in Bangla

Proceedings of the 12th Conference on Language Resources and Evaluation (LREC 2020), pages 2862–2871 Marseille, 11–16 May 2020 c⃝ European Language Resources Association (ELRA), licensed under CC-BY-NC 2862 BanFakeNews: A Dataset for Detecting Fake News in Bangla Md Zobaer Hossain†♣, Md Ashraful Rahman†♣, Md Saiful Islam♣, Sudipta Kar♠ ♣ Shahjalal University of Science and Technology, Sylhet, Bangladesh {zobaer37, ashraful54}@student.sust.edu, saiful-cse@sust.edu ♠ University of Houston, Texas, USA skar3@uh.edu Abstract 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. The dataset and source code are publicly available at https://github.com/Rowan1697/FakeNews. Keywords: Fake news, Bangla, Low Resource Language 1. Introduction Articles that can potentially mislead or deceive readers by providing fabricated information are known as fake news. Usually fake news are written and published with the in- tent to damage the reputation of an agency, entity, or per- son1. The popularity of social media (e.g. Facebook), easy access to online advertisement revenue, increased political divergence have been the reasons for the spread of fake news. Hostile government actors have also been implicated in generating and propagating fake news, particularly dur- ing elections and protests (TUFEKCI, 2018) to manipulate people for personal and organizational gains. Impact of Fake news is creating havoc worldwide. During the 2016 US election, 25 percent of the Americans visited a fake news website in a six-week period of election which has been hypothesized as one of the issues that influenced the final results (Grave et al., 2018). In Bangladesh, the 2012 Ramu incident is an exemplary event where almost 25 thousand people participated in destroying the Buddhist temples on the basis of a Facebook post from a fake account (Manik, 2012). About 12 Buddhist temples and monaster- ies and 50 houses were destroyed by the angry mob. Fake news that contains blasphemy can easily repeat these types of incidents where people are very sentimental to their reli- gions. To tackle fake news there are some dedicated websites like www.politifact.com, www.factcheck.org, www.jaachai.com where they manually update poten- tial fake news stories published in online media with log- ical and factual explanations behind the news being …

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