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Research Article

JCR. 2020; 7(9): 452-460


SENTIMENT ANALYSIS OF CASCADING TWITTER DATA USING HADOOP ECO SYSTEM APPROACHES

Ashok Kumar Nanduri, G.L. Sravanthi, K. Siva Kumar, K V K V L Pavan Kumar.

Abstract
Sentimental analysis is defined as a process of recognizing and grouping the opinions of users based on their view conveyed regarding particular parts or different parts of information. Twitter is being used for finding the people’s opinion on trending concept which is popular these days. According to the suggested approach, the live information of twitter is collected by the configuration of the system by Hive ware, sqoop, Hadoop, and Flume. The agent of the flume is
used for setting the keyword file on the cluster of Hadoop to getting similar information, after that the gathered data is synced on HDFS (Hadoop Distributed File Systems). In the sentimental analysis, the application of twitter information, builds a Hive’s database, and the gathered data is imported into the table of Hive and then the data is compared along the dictionary data set of AFINN. The results which are acquired after executing the sentimental analysis on tweets, these are classified into the opinions of negative & positive. For making the decision, the negative and positive values that are obtained from tweets are used.

Key words: Scoop, Meta store, Sentiment Analysis, Big data, Twitter, Hadoop, Cluster, Flume, Hive, HDFS.



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