Abstract

Twitter is an online social networking site which contains rich amount of data that can be a structured, semi-structured and un-structured data. In this work, a method which performs classification of tweet sentiment in Twitter is discussed. To improve its scalability and efficiency, it is proposed to implement the work on Hadoop Ecosystem, a widely-adopted distributed processing platform using the Map Reduce parallel processing paradigm. Finally, extensive experiments will be conducted on real-world data sets, with an expectation to achieve comparable or greater accuracy than the proposed techniques in literature.

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