The recent advancements in technology and the widespread availability of information, has made it easier to reach massive audiences. However, the issue of fake news has reached a breaking point. It not only harms online social networks and news sites but also negatively impacts offline communities. Over the past few years, researchers have been challenged by the dangerous influence of fake news on politics, culture, and lifestyle, and now with the COVID-19 pandemic, the danger has extended to health and social well-being. Immediate action is necessary to counteract this problem. Therefore, the goal of this paper is to explore possible solutions to the problem of fake news and develop a suitable, effective, and user-friendly application that can identify disinformation and fake news by optimizing cloud-based tools. To achieve this, various papers and databases were analyzed, and it was concluded that a cloud-hosted web application and machine learning classifier would be a practical solution. The proposed model was implemented, and the results showed an accuracy rate of 93%.
Hasimi, Lumbardha and Poniszewska-Marańda, Aneta, "Cloud Optimization for Disinformation Detection and News Veracity" (2023). WISP 2023 Proceedings. 2.