IMHO, I disagree. The problem is taking an entire article not filtering the emotions out of it, tallying emotional hits and drives a score. If the article has a high degree of emotional identifiers its most likely an opinion piece not an entirely factual news article. Then articles from the same agency that has low repeatedly scores (or writers) would be flagged.<p>Use media bias checker, pick the far left and far right news/blog agencies, train them on picking out emotions arguments first, then statements of facts.<p>We train AI with xrays at work. Humans identify the issues on scans, then the software learns from humans identification on the xrays. After training, it can start to recognize what humans are identifying. Text has meaning, so you have to defuzz the text into something simpler.