  The evolution of the information and communication technologies has
dramatically increased the number of people with access to the Internet, which
has changed the way the information is consumed. As a consequence of the above,
fake news have become one of the major concerns because its potential to
destabilize governments, which makes them a potential danger to modern society.
An example of this can be found in the US. electoral campaign, where the term
"fake news" gained great notoriety due to the influence of the hoaxes in the
final result of these. In this work the feasibility of applying deep learning
techniques to discriminate fake news on the Internet using only their text is
studied. In order to accomplish that, three different neural network
architectures are proposed, one of them based on BERT, a modern language model
created by Google which achieves state-of-the-art results.
