  Recent years have seen an explosion in social media usage, allowing people to
connect with others. Since the appearance of platforms such as Facebook and
Twitter, such platforms influence how we speak, think, and behave. This problem
negatively undermines confidence in content because of the existence of fake
news. For instance, false news was a determining factor in influencing the
outcome of the U.S. presidential election and other sites. Because this
information is so harmful, it is essential to make sure we have the necessary
tools to detect and resist it. We applied Bidirectional Long Short-Term Memory
(Bi-LSTM) to determine if the news is false or real in order to showcase this
study. A number of foreign websites and newspapers were used for data
collection. After creating & running the model, the work achieved 84% model
accuracy and 62.0 F1-macro scores with training data.
