No need to apologize. I'm actually not using a generative classifier like Bayes. I'm using Conditional Random Fields which is a discriminative classifier. I found that based on my training set, CRF produced higher accuracy.

That being said, I've also thought of way more ways to make the processing of the articles a lot better. I had an idea using an LSTM and another idea which would use an RNN to map the sensational article to a non-sensational article. The only problem with some of these approaches is that they would require someone to read an article and write a non-biased form of the article.

I do like your approach, do you have any results from what you've found tinkering around?