An efficient framework for real-time tweet classification

被引:9
|
作者
Khan I. [1 ]
Naqvi S.K. [1 ]
Alam M. [2 ]
Rizvi S.N.A. [3 ]
机构
[1] Center for Information Technology, Jamia Millia Islamia, New Delhi
[2] Department of Computer Science, Jamia Millia Islamia, New Delhi
[3] Department of Mathematics, Jamia Millia Islamia, New Delhi
关键词
Apache Spark; Big Data; HDFS; RDDs;
D O I
10.1007/s41870-017-0015-x
中图分类号
学科分类号
摘要
Increasing popularity of social networking sites like facebook, twitter, google+ etc. is contributing in fast proliferation of big data. Amongst social Networking sites, twitter is one of the most common source of big data where people from across the world share their views on various topics and subjects. With daily Active user count of 100-million+ users twitter is becoming a rich information source for finding trends and current happenings around the world. Twitter does provide a limited “trends” feature. To make twitter trends more interesting and informative, in this paper we propose a framework that can analyze twitter data and classify tweets on some specific subject to generate trends. We illustrate the use of framework by analyzing the tweets on “Politics” domain as a subject. In order to classify tweets we propose a tweet classification algorithm that efficiently classify the tweets. © 2017, Bharati Vidyapeeth's Institute of Computer Applications and Management.
引用
收藏
页码:215 / 221
页数:6
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