In the simplest case, we might have pair-wise constraints on whether two pieces of text have the same viewpoints (i.e., liked or disliked by the same rater), which would yield a different learning problem akin to the metric learning problem; note, however, the complication that two pieces of text receiving different labels from a given user might not necessarily contain contrasting viewpoints.
rather than trying to reduce this problem to a set of known text classification tasks, we address this task via a collaborative filtering framework that incorporates textual features.