MRI
MRI India Journals Vol. 3 No. 2 (2016): Volume 3 Issue 2 2016

SOCIAL MEDIA DATA ANALYSIS USING HADOOP

Authors

  • Pratik Dhotre
  • Harshal Gawali
  • Trupti Thore
  • Prasad Govardhankar
  • Ila Savant

DOI:

https://doi.org/10.65521/mjret.v3i2.1040

Keywords:

Twitter API, Hashtag Sentiment Hadoop HDFS Apache Flume NLP

Abstract

As of now we know present industries and some survey companies are mainly taking decisions by data obtained from web. As we see WWW is a rich collection of data that is mainly in the form of unstructured data from which we can do analysis on those data which is collected on some situation or on a particular thing. In this paper, we are going to talk how effectively sentiment analysis is done on the data which is collected from the Twitter using Flume. Twitter is an online web application which contains rich amount of data that can be a structured, semi-structured and un-structured data. We can collect the data from the twitter by using BIGDATA eco-system using online streaming tool Flume. And doing analysis on Twitter is also difficult due to language that is used for comments. And, coming to analysis there are different types of analysis that can be done on the collected data, So here we are taking sentiment analysis. Here we have categorized this sentiment analysis into 3 groups like tweets that are having positive, moderate and negative comment

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Published

2016-04-02

How to Cite

Dhotre, P., Gawali, H., Thore, T., Govardhankar, P., & Savant, I. (2016). SOCIAL MEDIA DATA ANALYSIS USING HADOOP. Multidisciplinary Journal of Research in Engineering and Technology, 3(2), 971–976. https://doi.org/10.65521/mjret.v3i2.1040

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