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Framework for Analyzing User Behavior Using Big Data Technology

Advent of social media like Facebook and Twitter has played the role of the multiplier in adding the data on the web. Due to expeditious enlargement of the web, shopping and trading through e-commerce is on demand and accepted by people everywhere. Now a day's people use the internet to study and analyze the information about an article by reading various reviews about that article before purchasing it online. We can understand the customer behavior easily by observing and understanding social media data. After studying the behavior of user's country wise we can predict current trends that can be used in deciding usefulness of some tasks, product, and themes. But there are several challenges which create obstacles in analyzing the exact meaning of sentiments. We have addressed various significant challenges and a system has been designed to analyze sentiments with an aim to resolve many of listed issue. In this paper, sentiment analysis is performed on a large dataset of tweets using big data platform. By analyzing the user social data about a particular topic we have performed analysis to depict the user's behavior for a particular topic in certain country and city.