An essential element of sentiment mining, and other attitudinal analyses of textual data, is the notion of subjectivity. I've been re-reading some publications by Janyce Wiebe and others on the topic - in the process of performing a more extensive literature survey of the field. Something that strikes as being problematic about current definitions is that they attempt to have two distinct categories (subjectivity and objectivity) which are to be used as labels for spans of text.
Firstly, I think that subjectivity is not a feature of the text, but the intention of the author(s). Secondly, I believe that one can (ideally) measure the difference between what is 'true' and what is understood by the reader of the text. Thirdly, I believe that spans of text can intermix what we traditionally might regard as being subjective and objective intentions.
For example, consider the following:
The idiot won the election.
It may be factually correct that some person (referred to by the phrase 'the idiot') won some election (referred to by 'the election'). However, the term 'idiot' indicates a certain about of subjectivity. The author may wish to express regret by reporting factual information in an opinionated manner. It may also be the case that that particular person didn't win the election (though the author believes that he did). In this case, the author's intention is to be objective, though in fact they are simply mistaken.