  Understanding expressions of emotions in support forums has considerable
value and NLP methods are key to automating this. Many approaches
understandably use subjective categories which are more fine-grained than a
straightforward polarity-based spectrum. However, the definition of such
categories is non-trivial and, in fact, we argue for a need to incorporate
communicative elements even beyond subjectivity. To support our position, we
report experiments on a sentiment-labelled corpus of posts taken from a medical
support forum. We argue that not only is a more fine-grained approach to text
analysis important, but simultaneously recognising the social function behind
affective expressions enable a more accurate and valuable level of
understanding.
