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With the outbreak of the Covid-19 virus, the activity of users on Twitter has significantly increased. Some studies have investigated the hot topics of tweets in this period; however, little attention has been paid to presenting and…

This paper proposes a methodology for exploring how linguistic behaviour on social media can be used to explore societal reactions to important events such as those that transpired during the SARS CoV2 pandemic. In particular, where spatial…

The outbreak of covid-19 started many months ago, the reported origin was in Wuhan Market, China. Fastly, this virus was propagated to other countries because the access to international travels is affordable and many countries have a…

As the COVID-19 pandemic swept over the world, people discussed facts, expressed opinions, and shared sentiments on social media. Since the reaction to COVID-19 in different locations may be tied to local cases, government regulations,…

The COVID-19 pandemic brought upon a massive wave of disinformation, exacerbating polarization in the increasingly divided landscape of online discourse. In this context, popular social media users play a major role, as they have the…

The COVID-19 pandemic has produced a flurry of online activity on social media sites. As such, analysis of social media data during the COVID-19 pandemic can produce unique insights into discussion topics and how those topics evolve over…

The COVID-19 pandemic has had adverse effects on both physical and mental health. During this pandemic, numerous studies have focused on gaining insights into health-related perspectives from social media. In this study, our primary…

This paper formulates the problem of dynamically identifying key topics with proper labels from COVID-19 Tweets to provide an overview of wider public opinion. Nowadays, social media is one of the best ways to connect people through…

As the COVID-19 ravaging through the globe, accurate forecasts of the disease spread is crucial for situational awareness, resource allocation, and public health decision-making. Alternative to the traditional disease surveillance data…

Social media platforms, such as Twitter, provide a suitable avenue for users (people or patients) concerned on health questions to discuss and share information with each other. In December 2019, a few coronavirus disease cases were first…

Many in the US were reluctant to report their COVID-19 cases at the height of the pandemic (e.g., for fear of missing work or other obligations due to quarantine mandates). Other methods such as using public social media data can therefore…

The COVID-19 pandemic has created widespread health and economical impacts, affecting millions around the world. To better understand these impacts, we present the TweetCOVID system that offers the capability to understand the public…

The global world is crossing a pandemic situation where this is a catastrophic outbreak of Respiratory Syndrome recognized as COVID-19. This is a global threat all over the 212 countries that people every day meet with mighty situations. On…

The COVID-19 pandemic has been a global health crisis playing out in the age of social media. Even though the virtual environment makes interaction possible regardless of physical location, many of the most pressing issues during the…

Epidemiological models, traditionally used to study disease spread, can effectively analyze mob behavior on social media by treating ideas, sentiments, or behaviors as ``contagions" that propagate through user networks. In this research, we…

Crises such as natural disasters, global pandemics, and social unrest continuously threaten our world and emotionally affect millions of people worldwide in distinct ways. Understanding emotions that people express during large-scale crises…

The coronavirus disease 2019 (COVID-19) has become a public health emergency of international concern affecting more than 200 countries and territories worldwide. As of September 30, 2020, it has caused a pandemic outbreak with more than 33…

We describe Mega-COV, a billion-scale dataset from Twitter for studying COVID-19. The dataset is diverse (covers 268 countries), longitudinal (goes as back as 2007), multilingual (comes in 100+ languages), and has a significant number of…

This paper describes a large global dataset on people's discourse and responses to the COVID-19 pandemic over the Twitter platform. From 28 January 2020 to 1 June 2022, we collected and processed over 252 million Twitter posts from more…

During a disease outbreak, timely non-medical interventions are critical in preventing the disease from growing into an epidemic and ultimately a pandemic. However, taking quick measures requires the capability to detect the early warning…