论文标题
你被误导了吗？一项研究在Facebook上孟加拉的COVID相关假新闻
Are You Misinformed? A Study of Covid-Related Fake News in Bengali on Facebook
论文作者
论文摘要
我们对生活的看法和生活的看法可以通过我们如何看待他人在Facebook等社交媒体上的观点来塑造。当我们与他人建立联系的方法更少时，这种依赖性增加了。但是，与Covid-19有关的假新闻已成为Facebook上的一个重大问题。孟加拉语是全球第七种口语的第七语言，但我们没有意识到以前没有研究Covid-19在Facebook上与孟加拉语相关的假新闻的普遍性。在本文中，我们开发了机器学习模型，以自动检测孟加拉语的假新闻。表现最好的模型是BERT，F1得分为0.97。我们将BERT应用于与Covid-19有关的所有Facebook孟加拉帖子。我们在COVID-19-Bengali假新闻中发现了10个主题，分为三类：系统（例如，医学系统），信仰（例如宗教仪式）和社会（例如，科学意识）。
Our opinions and views of life can be shaped by how we perceive the opinions of others on social media like Facebook. This dependence has increased during COVID-19 periods when we have fewer means to connect with others. However, fake news related to COVID-19 has become a significant problem on Facebook. Bengali is the seventh most spoken language worldwide, yet we are aware of no previous research that studied the prevalence of COVID-19 related fake news in Bengali on Facebook. In this paper, we develop machine learning models to detect fake news in Bengali automatically. The best performing model is BERT, with an F1-score of 0.97. We apply BERT on all Facebook Bengali posts related to COVID-19. We find 10 topics in the COVID-19 Bengali fake news grouped into three categories: System (e.g., medical system), belief (e.g., religious rituals), and social (e.g., scientific awareness).
