A text classification project for validating if a news article consists of false climate change news.

The system was build using Natural Language Processing techniques and Neural Networks in Python. Feature engineering was done using entity recognition, Part-of-speech tagging, n-grams generator, text polarity recognition using SpaCy library. Pre-trained word embeddings ‘glove’ was also used for deep learning models like RNN and LSTM. The models were then evaluated based on F1 score and recall.