7- Language Independent Sentiment Analysis
Published in IEEE International Conference on Advances in the Emerging Computing Technologies (AECT), 2020
Recommended citation: Muhammad Haroon Shakeel, Safi Faizullah, Turki Alghamidi, Imdadullah Khan (2020). Language Independent Sentiment Analysis. IEEE International Conference on Advances in the Emerging Computing Technologies (AECT). https://arxiv.org/pdf/1912.11973
Abstract: 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.