There's actually beeen some work on bayesian reasoning, and how if people start with probability distributions that are far enough apart, collecting more data doesn't necessarily drive them toward convergence -- if you're fairly convinced that X is crooked, while I think he's the bees knees, then it is "rational" for me to consider news sources explaining his crookedness as coming from a vast conspiracy theory, which increases my distrust for those news sources. If other sources are reporting that's hogwash, I'll again do bayesian updating that increases my trust in them. With the right set of data, and starting point, either position can get more and more reinforced.

That is a literature about if you start with different priors and get the same info, you might not converge in opinion. I'm focused on the situation where you have the same prior and get different info. Robin Hanson