Related papers: The COVID That Wasn't: Counterfactual Journalism U…

The objective of this work is to explore popular discourse about the COVID-19 pandemic and policies implemented to manage it. Using Natural Language Processing, Text Mining, and Network Analysis to analyze corpus of tweets that relate to…

The present paper is about the participation of our team "techno" on CERIST'22 shared tasks. We used an available dataset "task1.c" related to covid-19 pandemic. It comprises 4128 tweets for sentiment analysis task and 8661 tweets for fake…

COVID-19 has resulted in an ongoing pandemic and as of 12 June 2020, has caused more than 7.4 million cases and over 418,000 deaths. The highly dynamic and rapidly evolving situation with COVID-19 has made it difficult to access accurate,…

The COVID-19 pandemic has had a huge impact on various areas of human life. Hence, the coronavirus pandemic and its consequences are being actively discussed on social media. However, not all social media posts are truthful. Many of them…

The COVID-19 epidemic is considered as the global health crisis of the whole society and the greatest challenge mankind faced since World War Two. Unfortunately, the fake news about COVID-19 is spreading as fast as the virus itself. The…

COVID-19 is one of the most important topic these days, specifically on search engines and news. While fake news are easily shared, scientific papers are reliable sources where information can be extracted. With about 24,000 scientific…

This study investigates the linguistic traits of fake news and real news. There are two parts to this study: text data and speech data. The text data for this study consisted of 6420 COVID-19 related tweets re-filtered from Patwa et al.…

The COVID-19 pandemic has affected people's lives in many ways. Social media data can reveal public perceptions and experience with respect to the pandemic, and also reveal factors that hamper or support efforts to curb global spread of the…

Humanity is battling one of the most deleterious virus in modern history, the COVID-19 pandemic, but along with the pandemic there's an infodemic permeating the pupil and society with misinformation which exacerbates the current malady. We…

Quantifying the characteristics of public attention is an essential prerequisite for appropriate crisis management during severe events such as pandemics. For this purpose, we propose language-agnostic tweet representations to perform…

The global pandemic of COVID-19 has made the public pay close attention to related news, covering various domains, such as sanitation, treatment, and effects on education. Meanwhile, the COVID-19 condition is very different among the…

A drastic rise in potentially life-threatening misinformation has been a by-product of the COVID-19 pandemic. Computational support to identify false information within the massive body of data on the topic is crucial to prevent harm.…

Researches about COVID-19 has increased largely, no matter in the biology field or the others. This research conducted a text analysis using LDA topic model. We firstly scraped totally 1127 articles and 5563 comments on SCMP covering…

The COVID-19 pandemic has caused a global health crisis that affects many aspects of human lives. In the absence of vaccines and antivirals, several behavioural change and policy initiatives, such as physical distancing, have been…

With the pandemic of COVID-19, relevant fake news is spreading all over the sky throughout the social media. Believing in them without discrimination can cause great trouble to people's life. However, universal language models may perform…

During the COVID-19 pandemic, the news media coverage encompassed a wide range of topics that includes viral transmission, allocation of medical resources, and government response measures. There have been studies on sentiment analysis of…

The COVID-19 pandemic led to an infodemic where an overwhelming amount of COVID-19 related content was being disseminated at high velocity through social media. This made it challenging for citizens to differentiate between accurate and…

The increasingly rapid spread of information about COVID-19 on the web calls for automatic measures of quality assurance. In that context, we check the credibility of news content using selected linguistic features. We present two empirical…

The sharing of fake news and conspiracy theories on social media has wide-spread negative effects. By designing and applying different machine learning models, researchers have made progress in detecting fake news from text. However,…

Currently, the world is in the midst of a severe global pandemic, which has affected all aspects of people's lives. As a result, there is a deluge of COVID-related digital media articles published in the United States, due to the disparate…