Pros/Cons of stop word removal? What are the pros / cons of removing stop words from text in the context of a text classification problem, I'm wondering what the best approach is (i.e. to remove or not to remove)?

I've read somewhere (but can't locate the reference) that it may be detrimental the the performance of a model in the case of sentiment analysis to remove stop words.
In the context of sentiment analysis, removing stop words can be problematic if context is affected. For example suppose your stop word corpus includes ‘not’, which is a negation that can alter the valence of the passage. So you have to be cautious of exactly what is being dropped and what consequences it can have.