A recent endeavor of mine requires asking users how related two concepts are. Example: Kiwi and Fruit. Identical? Fairly Similar? Rather different? Unrelated?
It occurs to me that for certain combinations of terms (such as Strawberries and Tasty) people may have varying opinions. This, in effect, poses problems for an algorithm that tries to "average" the responses to get a global truth. Instead, it makes sense that for rather divergent answers one would have different niches or "universes of truth" that are self-consistent with the relationship data they provide.
One possible idea is that of basic context: if you live in a house you are likely to think of a chair as something to sit on, but if you live in Asia, floormats and cushions on the ground may satisfy that "idea" so which one is correct? Both are correct for their specific context.
So, given a bunch of relationships (Kiwi is a Fruit, Kiwi is Delicious, Kiwi is Not Delicious) divergent results will emerge. Are there any algorithms or studies that take this sort of divergence of tagging/labeling into account?