Language Independent Sentiment Analysis

Abstract

Social media platforms and online forums generate a 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 the applicability to a particular demographic and 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.