ABSTRACT
Since the outbreak of the novel SARS-CoV-2, i.e., in December 2019, in Wuhan, China, more than 110 million cases have been reported, with 2.5 million deaths worldwide. It is not the first time, earlier in 2002–2003 SARS-CoV and in 2010 MERS-CoV outbreaks were reported. However, in 2019 novel SARS-CoV-2 outbreak prevailed to a great extent worldwide. Still, we are in the middle of a pandemic and seek effective vaccines and therapeutics for prevention and complete cure, respectively. There are new strains of novel SARS-CoV2 reported in a different part of the world. Considering the research data and statistics from CDC and WHO, the novel SARS-CoV-2 is the second most deadly viral outbreak after the Spanish Flu in 1918. Compared to previous coronavirus outbreak cases, the novel SARS-CoV-2 attack was reported to be more transmissible but less fatal. Among the top five countries worst affected by novel SARS-CoV-2 infection and mortality are the United States, India, Brazil, Russia, and the United Kingdom. Similarly, many countries in Europe, including Spain and Italy have endured a similar impact with viral outbreaks. The pandemic started in China and traveled to Europe, the United States and the American continent, and many Asian countries, including Russia and India, which are “hot spots” for virus infection and disease outbreak. In the first wave of the virus outbreak, many countries including China, South Korea, Japan, New Zealand, etc., successfully controlled and contained the virus, using strict social distancing and other containment measures. The reproductive number (R 0) and fatality rate of COVID-19 disease caused by novel SARS-CoV-2 infection vary among different populations. However, infection and disease are a function of several risk factors, including age, sex, comorbidity, and strain of novel SARS-CoV-2. Simultaneously, there is a massive effort in research for diagnostic, therapeutic, and vaccine development. It was the first time in human history where a clinical diagnosis was implemented very early in the case of a pandemic. Several antiviral drugs, antiinflammatory agents, immune modulators, and vitamins were used to control the COVID-19 disease. © 2022 Elsevier Inc. All rights reserved.
ABSTRACT
Purpose: The rapid advancement of technology in online communication and fingertip access to the Internet has resulted in the expedited dissemination of fake news to engage a global audience at a low cost by news channels, freelance reporters and websites. Amid the coronavirus disease 2019 (COVID-19) pandemic, individuals are inflicted with these false and potentially harmful claims and stories, which may harm the vaccination process. Psychological studies reveal that the human ability to detect deception is only slightly better than chance;therefore, there is a growing need for serious consideration for developing automated strategies to combat fake news that traverses these platforms at an alarming rate. This paper systematically reviews the existing fake news detection technologies by exploring various machine learning and deep learning techniques pre- and post-pandemic, which has never been done before to the best of the authors’ knowledge. Design/methodology/approach: The detailed literature review on fake news detection is divided into three major parts. The authors searched papers no later than 2017 on fake news detection approaches on deep learning and machine learning. The papers were initially searched through the Google scholar platform, and they have been scrutinized for quality. The authors kept “Scopus” and “Web of Science” as quality indexing parameters. All research gaps and available databases, data pre-processing, feature extraction techniques and evaluation methods for current fake news detection technologies have been explored, illustrating them using tables, charts and trees. Findings: The paper is dissected into two approaches, namely machine learning and deep learning, to present a better understanding and a clear objective. Next, the authors present a viewpoint on which approach is better and future research trends, issues and challenges for researchers, given the relevance and urgency of a detailed and thorough analysis of existing models. This paper also delves into fake new detection during COVID-19, and it can be inferred that research and modeling are shifting toward the use of ensemble approaches. Originality/value: The study also identifies several novel automated web-based approaches used by researchers to assess the validity of pandemic news that have proven to be successful, although currently reported accuracy has not yet reached consistent levels in the real world. © 2021, Emerald Publishing Limited.