Effective Information Retrieval Framework for Twitter Data Analytics

The widespread adoption of opinion mining and sentiment analysis in higher cognitive processes encourages the need for real time processing social media data to capture insights about user's polarity, opinions, current trends. In recent years, lots studies were conducted around achieve accuracy. But reducing still remained challenging. Later, big technologies came into existence solve these challenges but those have its own set complexities along with having hardware deadweight on system. contribution this article is touch upon mentioned by presenting a climbable, quick fault tolerant framework process real-time extract hidden insights. This versatile enough support batch streams parallel distributed environment. Experimental proposed twitter posts concludes it as quicker, robust, tolerant, comparatively more accurate traditional approaches.