The worldwide spread of COVID-19 has prompted extensive online discussions, creating an `infodemic' on social media platforms such as WhatsApp and Twitter. However, the information shared on these platforms is prone to be unreliable and/or misleading. In this paper, we present the first analysis of COVID-19 discourse on public WhatsApp groups from Pakistan. Building on a large scale annotation of thousands of messages containing text and images, we identify the main categories of discussion. We focus on COVID-19 messages and understand the different types of images/text messages being propagated. By exploring user behavior related to COVID messages, we inspect how misinformation is spread. Finally, by quantifying the flow of information across WhatsApp and Twitter, we show how information spreads across platforms and how WhatsApp acts as a source for much of the information shared on Twitter.
翻译：COVID-19在世界各地的传播引发了广泛的在线讨论,在诸如WhessApp和Twitter等社交媒体平台上创建了一个“信息”平台,然而,这些平台上共享的信息容易不可靠和/或误导。我们在本文件中首次分析了COVID-19关于巴基斯坦公众的WhoesApp团体的讨论。在对包含文本和图像的数千条信息进行大规模批注的基础上,我们确定了讨论的主要类别。我们侧重于COVID-19信息,并了解所传播的图像/文本信息的不同类型。通过探索与COVID信息有关的用户行为,我们检查错误信息是如何传播的。最后,通过量化PhesApp和Twitter的信息流,我们展示了信息如何在平台上传播,以及什么App如何成为在推特上分享的大部分信息的源。
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