Sentimental Analysis on Twitter using Pig and Hive
Ajit Noonia1, Vikas Verma2, Ruchika Khandelwal3, Kushagra Gautam4

1Ajit Noonia*, Chitkara University Institute of Engineering and Technology, Chitkara University, Punjab, India.
2Vikas Verma, Assistant Professor, Department of Computer Science and Engineering, Jaipur National University, Jaipur, India. Ruchika Khandelwal, Department of Computer Science and Engineering, Jaipur National University, Jaipur, India.
3Kushagra Gautam, Department of Computer Science and Engineering, Jaipur National University, Jaipur, India.
Manuscript received on December 13, 2019. | Revised Manuscript received on December 21, 2019. | Manuscript published on January 10, 2020. | PP: 237-240 | Volume-9 Issue-3, January 2020. | Retrieval Number: B7051129219/2020©BEIESP | DOI: 10.35940/ijitee.B7051.019320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: Data science is the analytic process to explore new prediction and pattern when to process the collected data. Data analysis is done using large sets of databases and due to them we can easily form patterns and then they could be recognized. This will helpful for prediction of new challenges and circumstances. From the perspective of statistics data analysis of large observational databases has very challenges which made it a research area in abroad as well as in India. Different tools are available in market to process and analyze the large set of data for prediction of future trends and due to which knowledgeable decision should be created. Bigdata and hadoop are one of them. In this paper we have collected 5000 above tweets and then we have done pre-processing over it and then done sentimental analysis so as to get negative and positive tweets and then done prediction over it so as to get the people’s sentiments over a particular person.
Keywords:   Big Data, Sentimental Analysis, tokenizer, hadoop, Apache hive, Apache pig, pre-processing.
Scope of the Article: Big Data