  Social media platforms and online forums generate rapid and increasing amount
of textual data. Businesses, government agencies, and media organizations seek
to perform sentiment analysis on this rich text data. The results of these
analytics are used for adapting marketing strategies, customizing products,
security and various other decision makings. Sentiment analysis has been
extensively studied and various methods have been developed for it with great
success. These methods, however apply to texts written in a specific language.
This limits applicability to a limited demographic and a specific geographic
region. In this paper we propose a general approach for sentiment analysis on
data containing texts from multiple languages. This enables all the
applications to utilize the results of sentiment analysis in a language
oblivious or language-independent fashion.
