Abstract: The use of machine learning has become widespread in recent years, especially due to the impact of media content on the general population. In particular, the validation of truth in the context of news has become a critical necessity, due to its ready availability from verified and unverified sources, and its ability to influence people majorly. The present work outlines a LSTM (long short-term memory) based approach to news validation. The results obtained by the model are presented in terms of the training data set and contrasted with the results obtained from the test data set. Appreciable accuracy is achieved through the model, seen through the corresponding loss curves and confusion matrix.

Keywords: Machine Learning, LSTM, News Validation, Loss Curves, Confusion Matrix.

| DOI: 10.17148/IJIREEICE.2020.8905