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@article{144435,
        author = {Kanha Shukla and Abhijeet Raj and Ankush Bansal and Rajkumar Singh Rathore},
        title = {Why Hadoop is a better platform for Large Scale Sentiment Analysis ?},
        journal = {International Journal of Innovative Research in Technology},
        year = {},
        volume = {3},
        number = {11},
        pages = {240-245},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=144435},
        abstract = {Sentiment analysis on Twitter data has attracted much attention recently. One of the system's key features, is the immediacy in communication with other users in an easy, user-friendly and fast way. Consequently, people tend to express their feelings freely, which makes Twitter an ideal source for accumulating a vast amount of opinions towards a wide diversity of topics. This amount of information offers huge potential and can be harnessed to receive the sentiment tendency towards these topics. Now with the case on the desk we have multiple platforms on which the Sentiment analysis can be done like oracle, Teradata, MySQL, Hadoop.  In this paper, we discuss the issue why hadoop is a better platform for large scale Sentiment analysis. With its extensively smart work division methodologies Hadoop here has emerged as the time as well as data efficient platform for performing large scale analysis.},
        keywords = {Hadoop, Sentiment Analysis, data partition, fault tolerant},
        month = {},
        }