Sentiment Analysis on Tweets

Abstract

The rapid increase of textual data is overwhelming. The huge amount of data generated from the different call sites, customer reviews on different products, and so on is in the unstructured form. So the amount of textual centre logs, emails, blogs, documents on the internet, tweets form twitter, customer comments from different social networking data rapidly increasing makes the summarization task challenging for businesses. In this paper we provide techniques that how to organize textual data and analyze textual data for extracting intuitive customer intelligence from a large collection of data. The predominant and different types of information on twitter make it one of the most appropriate virtual environments for information monitoring and tracking. In this paper, starting with the analysis of different hash-tags, categorization of different areas, identification of influence, and finally analysis of sentiment. This paper tries to draw some important conclusions based on the sentiment analyzed.