Use regression instead of classification for hard labeled ranking datasets Let's imagine I have a dataset of movie reviews with annotated sentiment:

-1 means negative
 0 means neutral
+1 means positive


I see a lot of people trying to do classification to try to answer those types of problems, but shouldn't regression be used instead? To me using regression would allow the system to model that there is a transition between labels, e.g. 0 is in between. Any thoughts on this?
An issue with regression is that the distance between negative, neutral and positive are not necessarily the same. This transition/uncertainty you mention can be modeled by using a probability distribution over the classes as opposed to a hard argmax. If you use Neural Networks for example the last softmax layer gives you this information for free (For example: 0.1 on Negative, 0.6 Neutral and 0.3 Positive).