Sentiment analysis systems are automated tools which analyze text extracts entered by users and attempt to classify them under different sentiment categories, namely under: positive, negative, or neutral emotion. Such systems are gaining increasing interest with a wide range of applications covering: blog sentiment analysis, client feedback analysis, and opinion mining on social media (with people expressing their opinions on social media websites, e.g. Facebook, Twitter, etc.). In this project, we introduce a tool titled LISA which performs Lexical Information-based Sentiment Analysis, covering not only positive, negative, and neutral sentiments, but rather spans a battery of affect classes from positive to negative as well as to more ambiguous emotions such as joy, sadness, love, anger, disgust and astonishment. Report in pdf