Social media platforms have become a perfect medium for fake news
spreading. Fake news can have a significant impact on the daily lives of
individuals, and in many cases it can cause violence. Thus, detecting
fake news has become vital. In addition, to that many state of the art
solutions, treat the fake news detection system as a black box. This
will result in low user trust,
In this Paper we explain four distinct approaches for fake news de tection on the twitter platform, using the Lime Library. Such ex plainability contrasts the performance of these different approaches.
Usually, when it comes to fake news detection, the standard evalua tion is done using accuracy, precision, recall, etc. We take a different
approach of evaluating these approaches based on explainability .
