Social Sentiment Analysis Using Fuzzy Logic Addressing context effect on sentiment analysis by fuzzy lexicon dynamism

Fuzzy Logic revolution started during 1965 by Prof Lotfi A. Zadeh [1], [2] have evolved uncertainty and indeterminacy analytics forever. Sentiment analysis of published content on social networks is an essential key to analyze and predict social engagement polarities determined by provider's attitude and viewpoint toward a subject, being a profile, topic or single post. This paper uses precious works of Prof Lotfi A. Zadeh to propose a quantitative sentiment calculation method by introducing fuzziness and context dynamism on language-specific lexicons found on published short informal textual content on three holistic contexts of owner, user and the post itself.