This is really neat by the way, thanks for producing this paper, I think it's an important area to start poking around in.
The model predicts that areas in which there is little evidence one way or the other available are the ones where incorrect beliefs could be sustained, particularly when the belief is held by those around you.
I guess one interesting characteristic of certain superstitions is that people will avoid the scenario that they think will lead to a bad outcome, so they actually don't collect personal evidence discrediting that superstition.
This line of argument suggests that positive superstitions should be less persistent than negative superstitions, though I am not sure if that is true.
One mechanism I've heard posited (by Friston's neurosci lab) for how humans deal with noisy environments is to weight our sensory inputs by their expected precision. I might look at the ocean's surface and expect to see a froth of sea-foam, particulate matter, and water, so I won't pay enough attention to see a camouflaged fish. I'll still notice if Godzilla walks up out of it, though.
Would a similar precision-weighting mechanism help to model social trust, and to thus give us an idea of how groups can fixate on incorrect group-beliefs? Are people treating outgroup members or "opponents", so to speak, as uselessly noisy, and thus down-weighting any need to update based on what those persons say or do? Could this contribute to people's (supposed) occasional failures to accurately model their outgroups, since they're intuitively modelling those outgroups precisely as mostly outputting random noise rather than precise information?
It's possible that it's something along the lines you say. Another possibility is people just don't have good estimates of popularity among people they don't know, so they overestimate the popularity of opinions represented in their immediate networks.