  Traditional sentiment analysis often uses sentiment dictionary to extract
sentiment information in text and classify documents. However, emerging
informal words and phrases in user generated content call for analysis aware to
the context. Usually, they have special meanings in a particular context.
Because of its great performance in representing inter-word relation, we use
sentiment word vectors to identify the special words. Based on the distributed
language model word2vec, in this paper we represent a novel method about
sentiment representation of word under particular context, to be detailed, to
identify the words with abnormal sentiment polarity in long answers. Result
shows the improved model shows better performance in representing the words
with special meaning, while keep doing well in representing special idiomatic
pattern. Finally, we will discuss the meaning of vectors representing in the
field of sentiment, which may be different from general object-based
conditions.
