UGC Approved Journal no 63975(19)

ISSN: 2349-5162 | ESTD Year : 2014
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Published in:

Volume 4 Issue 7
August-2017
eISSN: 2349-5162

UGC and ISSN approved 7.95 impact factor UGC Approved Journal no 63975

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Published Paper ID:
JETIR1707033


Registration ID:
170533

Page Number

165-168

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Title

REVIEW OF SENTIMENT ANALYSIS USING TWITTER AND BIG DATA

Abstract

In this paper we propse a joint classification for tweets using big data and and social networking site twitter. Today classification using tweets is generally done by splitting a tweet in to words and not the whole tweet is taken in to consideration so we thought of introducing a novel approach where tweets will be classified as whole and not in words. To enhance the concept we thought of using big data technology such as APACHE SPARK to help in classification as the tweets that are retrieved are in large numbers and not easy for a single machine to handle them. The analyzed information results that are returned will be assembled together on a single machine and the prediction returned are in the form of sentiment analysis as each tweet as a whole will have score and various sentiments will be attached with them.

Key Words

Keywords :- Tweet, Segmentation, machine learning, Sentiment analysis, Sentiment classification, Big data.

Cite This Article

"REVIEW OF SENTIMENT ANALYSIS USING TWITTER AND BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.4, Issue 7, page no.165-168, August-2017, Available :http://www.jetir.org/papers/JETIR1707033.pdf

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2349-5162 | Impact Factor 7.95 Calculate by Google Scholar

An International Scholarly Open Access Journal, Peer-Reviewed, Refereed Journal Impact Factor 7.95 Calculate by Google Scholar and Semantic Scholar | AI-Powered Research Tool, Multidisciplinary, Monthly, Multilanguage Journal Indexing in All Major Database & Metadata, Citation Generator

Cite This Article

"REVIEW OF SENTIMENT ANALYSIS USING TWITTER AND BIG DATA", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.4, Issue 7, page no. pp165-168, August-2017, Available at : http://www.jetir.org/papers/JETIR1707033.pdf

Publication Details

Published Paper ID: JETIR1707033
Registration ID: 170533
Published In: Volume 4 | Issue 7 | Year August-2017
DOI (Digital Object Identifier):
Page No: 165-168
Country: loni, Maharashtra, India .
Area: Engineering
ISSN Number: 2349-5162
Publisher: IJ Publication


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