학술논문
A First Look at COVID-19 Messages on WhatsApp in Pakistan
Document Type
Conference
Author
Source
2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) Advances in Social Networks Analysis and Mining (ASONAM), 2020 IEEE/ACM International Conference on. :118-125 Dec, 2020
Subject
Language
ISSN
2473-991X
Abstract
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.