Sentiment analysis of figurative language in political tweets

I aim to develop a sentiment analysis sub-tool for classifying the polarity of political tweets containing figurative language (most likely idioms and fossilised metaphors). From a linguistic perspective, figurative language is hugely prevalent in tweets: it is concise, catchy, and gets the point across. From a computational perspective: idioms and metaphors and notoriously difficult to classify due to their heterogeneous nature. However, careful annotation and methods like the MWE tokenizer (NLTK) can successfully tackle this challenge.