Related papers: Twitter conversations predict the daily confirmed …

Doctors and nurses in these weeks are busy in the trenches, fighting against a new invisible enemy: Covid-19. Cities are locked down and civilians are besieged in their own homes, to prevent the spreading of the virus. War-related…

With the spiraling pandemic of the Coronavirus Disease 2019 (COVID-19), it has becoming inherently important to disseminate accurate and timely information about the disease. Due to the ubiquity of Internet connectivity and smart devices,…

We construct a novel database containing hundreds of thousands geotagged messages related to the COVID-19 pandemic sent on Twitter. We create a daily index of social distancing -- at the state level -- to capture social distancing beliefs…

With the world-wide development of 2019 novel coronavirus, although WHO has officially announced the disease as COVID-19, one controversial term - "Chinese Virus" is still being used by a great number of people. In the meantime, global…

Situated in the global outbreak of COVID-19, our study enriches the discussion concerning the emergent racism and xenophobia on social media. With big data extracted from Twitter, we focus on the analysis of negative sentiment reflected in…

The role of social media in information dissemination and agenda-setting has significantly expanded in recent years. By offering real-time interactions, online platforms have become invaluable tools for studying societal responses to…

The COVID-19 pandemic brought many challenges, from hospital-occupation management to lock-down mental-health repercussions such as anxiety or depression. In this work, we present a solution for the later problem by developing a Twitter…

The COVID-19 Omicron variant, reported to be the most immune evasive variant of COVID-19, is resulting in a surge of COVID-19 cases globally. This has caused schools, colleges, and universities in different parts of the world to transition…

Interaction-driven modeling of diseases over real-world contact data has been shown to promote the understanding of the spread of diseases in communities. This temporal modeling follows the path-preserving order and timing of the contacts,…

To increase situational awareness and support evidence-based policy-making, we formulated two types of mathematical models for COVID-19 transmission within a regional population. One is a fitting function that can be calibrated to reproduce…

The global impact of the COVID-19 pandemic has highlighted the need for a comprehensive understanding of public sentiment and reactions. Despite the availability of numerous public datasets on COVID-19, some reaching volumes of up to 100…

In the contemporary era, social media platforms amass an extensive volume of social data contributed by their users. In order to promptly grasp the opinions and emotional inclinations of individuals regarding a product or event, it becomes…

The outbreak of the novel coronavirus disease 2019 (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has been continuously affecting human lives and communities around the world in many ways, from cities…

The coronavirus disease (COVID-19) continues to have devastating effects across the globe. No nation has been free from the uncertainty brought by this pandemic. The health, social and economic tolls associated with it are causing strong…

Classical epidemiological models assume homogeneous populations. There have been important extensions to model heterogeneous populations, when the identity of the sub-populations is known, such as age group or geographical location. Here,…

Twitter is becoming an increasingly important platform for disseminating information during crisis situations, such as the COVID-19 pandemic. Effective crisis communication on Twitter can shape the public perception of the crisis, influence…

In this paper, we present ArCOV-19, an Arabic COVID-19 Twitter dataset that spans one year, covering the period from 27th of January 2020 till 31st of January 2021. ArCOV-19 is the first publicly-available Arabic Twitter dataset covering…

Over the past few months, there were huge numbers of circulating tweets and discussions about Coronavirus (COVID-19) in the Arab region. It is important for policy makers and many people to identify types of shared tweets to better…

The COVID-19 pandemic has introduced new opportunities for health communication, including an increase in the public use of online outlets for health-related emotions. People have turned to social media networks to share sentiments related…

Technology is uniquely positioned to help us analyze large amounts of information to provide valuable insight during widespread public health concerns, like the ongoing COVID-19 pandemic. In fact, information technology companies like Apple…