TITLE:
Towards Immunizing Infodemic: Comprehensive Study on Assessing the Role of Artificial Intelligence and COVID-19 Pandemic
AUTHORS:
Maryam Roshanaei, Greggory Sywulak
KEYWORDS:
Artificial Intelligence, Infodemic, Disinformation, COVID-19 Pandemic
JOURNAL NAME:
Journal of Intelligent Learning Systems and Applications,
Vol.14 No.3,
August
31,
2022
ABSTRACT: Artificial Intelligence (AI) technologies have intentionally and unintentionally been used to spread false information on all different types of subjects. Throughout the COVID-19 pandemic, there was a pool of different information that was being presented to the public, a lot of it contradicting one another. False information spreads regardless of whether there is intent to mislead or misinform whereas AI is not able to decipher what type of information it is pushing to the public is correct and what is not. This mass spread of information through online platforms has been coined as an Infodemic where it is considered a massive volume of information, both online and offline. It includes deliberate attempts to disseminate false information to undermine the public health response and advance alternative agendas of groups or individuals. An infodemic can be incredibly dangerous to society greatly affecting the ability of communities, societies, and countries to control and stop the pandemic due to the abundance of different information in combating the health crisis. This article assesses and evaluates the role of Artificial Intelligence (AI) technologies in helping to spread disinformation during the COVID-19 pandemic. It reviews and evaluates the information curation in modern media, the relationship between AI and disinformation, and the challenges of disinformation campaigns. It further outlines the impact of social media platforms on infodemic and their influence in spreading disinformation during the COVID-19 pandemic. This article analyzes several data mining studies that used different machine learning techniques to identify the influence of disinformation tactics on the COVID-19 pandemic associated with the Twitter platform. It further continues exploring the investigation of the number of influential tweets, the type of users, the levels of credibility of URLs, and the type and effect of social media bots. Finally, the authors assess and conclude how disinformation is widely prevalent throughout social media during the COVID-19 pandemic as well as illustrate the surveys that categorize the prevalence of users involved in the conversation about disinformation separated by country including the percentage of users posting tweets and retweeting news URLs, and the future work in combating the rapid disinformation campaigns and their ethical implication impact.