Weighted Accuracy Algorithmic Approach In Counteracting Fake News And Disinformation
This addresses the issue of fake news and disinformation for internet users, but it appears incremental as it builds on existing machine learning algorithms without introducing a new paradigm.
The paper tackles the problem of fake news and disinformation by proposing a methodology that uses a constraint mechanism combining weighted accuracies of four machine learning algorithms for detection and reporting, but no concrete results or numbers are provided.
As the world is becoming more dependent on the internet for information exchange, some overzealous journalists, hackers, bloggers, individuals and organizations tend to abuse the gift of free information environment by polluting it with fake news, disinformation and pretentious content for their own agenda. Hence, there is the need to address the issue of fake news and disinformation with utmost seriousness. This paper proposes a methodology for fake news detection and reporting through a constraint mechanism that utilizes the combined weighted accuracies of four machine learning algorithms.