This document summarizes a research paper that proposes an unsupervised approach to adapt existing sentiment lexicons to the context and language used on Twitter. It captures the contextual semantics of words based on their surrounding context in tweets. This is used to update the prior sentiment orientation and strength of words in an existing Twitter sentiment lexicon called Thelwall-Lexicon. Experiments show the adapted lexicons improve sentiment classification performance on two Twitter datasets compared to the original lexicon.