The emergence of the Internet has transformed global communications,
making information accessible at unprecedented speeds. With the emergence of
social media, people can now connect, share and interact immediately with a
variety of content. However, the ease with which information can be exchanged
also facilitates the rapid spread of unverified rumors and false information. In
this work, we aim to track and detect rumors, and to this end, we will present a
model based on a deep learning approach using LSTM and RNN algorithms in
order to obtain the best possible classification and more accurate and valid
results.
