RTFA. It has nothing to do with user ratings, but a direct calculation on the phrases "Mexican restaurant", "Italian restaurant", and "Chinese restaurant" base

RTFA. It has nothing to do with user ratings, but a direct calculation on the phrases "Mexican restaurant", "Italian restaurant", and "Chinese restaurant" based on the corpus of material. Go further and follow the links. This example is specifically covered in the linked material. "Mexican" picks up a negative association from the corpus containing frequent mention of "illegal" (listed as a negative term) in close proximity to "Mexican", so the phrase "Mexican restaurant" gets rated less favorably than "Chinese restaurant". The underlying problem is that we're throwing text at math and pretending that we're building things that understand anything more than word proximity. Human beings that can actually understand context can be horribly biased; software that doesn't have the slightest inkling of context will produce twisted versions of our own biases.