Building a text classification model from scratch
To train a model on your collected data, you need to label your text first. For example, given a sentence


  Cats can fly.


It need to be labelled as 'Faked'. Otherwise your model wouldn't know how to classifier between 'Faked' and 'Not Faked'.  

However, labelling needs huge effort. So if your data doesn't have any label, I suggest you use a trained model to predict or train a model on an existing sentiment classification dataset. You can search on the Google for the appropriate model of sentiment analysis.