
		<paper>
			<loc>https://jjcit.org/paper/52</loc>
			<title>SENTIMENT ANALYSIS OF ELECTRONIC PRODUCT TWEETS USING BIG DATA FRAMEWORK</title>
			<doi>10.5455/jjcit.71-1546924503</doi>
			<authors>Sunil Kumar,Vartika Koolwal,Krishna Kumar Mohbey</authors>
			<keywords>Twitter,Spark,Big data,Flume,Sentiment analysis.</keywords>
			<citation>18</citation>
			<views>6552</views>
			<downloads>1825</downloads>
			<received_date>2019-01-08</received_date>
			<revised_date>2019-02-27</revised_date>
			<accepted_date>2019-03-13</accepted_date>
			<abstract>Nowadays, social  media has  become  more  popular due  to  the  advancement  of Internet  technologies and 
smartphone devices. Such platforms have generated interest among users to give their opinion. Social media-like 
Twitter- also  plays  an  important  role  for  business  companies. Based  on  customer  opinion  about  any  product, 
business  companies  came  to  know  more  about  customer  choices.  In  the  current  scenario,  millions  of  tweets  are 
generated  by  people  every  year.  But  handling  these  huge  unstructured  tweets  is  not  possible  through  the 
traditional  platform.  Therefore,  big  data  framework, such  as  Hadoop and Spark, is used to  handle  such  kind of 
large data. 
In  this  paper,  different  sale tweets  are  used  to analyze the  sentiments  of  customers  regarding  electronic 
products.  The  experimental  results  of  the  proposed  work  will  be  useful  for  various  business  companies  to take 
business decisions, which will further enhance the product sales.</abstract>
		</paper>


