@inproceedings{051b6b64b7bb4140a27f529a26c67415,
title = "A First Look at COVID-19 Messages on WhatsApp in Pakistan",
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.",
keywords = "COVID-19, Misinformation, Twitter, WhatsApp",
author = "Javed, {R. Tallal} and Shuja, {Mirza Elaaf} and Muhammad Usama and Junaid Qadir and Waleed Iqbal and Gareth Tyson and Ignacio Castro and Kiran Garimella",
note = "Publisher Copyright: {\textcopyright} 2020 IEEE.; 12th IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020 ; Conference date: 07-12-2020 Through 10-12-2020",
year = "2020",
month = dec,
day = "7",
doi = "10.1109/ASONAM49781.2020.9381360",
language = "English (US)",
series = "Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "118--125",
editor = "Martin Atzmuller and Michele Coscia and Rokia Missaoui",
booktitle = "Proceedings of the 2020 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ASONAM 2020",
address = "United States",
}