Sentiment analysis implies attitudes, which imply context. A robust sentiment analysis system must either be trained on a targeted corpus (in which entities/concepts and attitudes are well aligned) or include some way of establishing a more targeted context after having been trained on a general-purpose corpus.

That is to say, people generally aren't describing the physical material occupying a toilet in a corpus of movie reviews.

Presumably if you throw a realistic corpus of written text you will have much more occurrences of the idiom.

I imagine that someone using the word 'shit' to describe the brown stuff in the toilet is probably negatively inclined towards it. Someone discussing it in a more neutral context (like a doctor or scientist) would probably be more likely to say 'feces'