查看文章

Fake news and its consequences carry the potential of impacting different aspects of different entities, ranging from a citizen’s lifestyle to a country’s global relations, there are many related works for collecting and determining fake news, but no reliable system is commercially available. This study aims to propose a deep learning model which predicts the nature of an article when given as an input. It solely uses text processing and is insensitive to history and credibility of the author or the source. In this paper, authors have discussed and experimented using word embedding (GloVe) for text pre-processing in order to construct a vector space of words and establish a lingual relationship. The proposed model which is the blend of convolutional neural network and recurrent neural networks architecture has achieved benchmark results in fake news prediction, with the utility of word embeddings complementing the …