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An Improved Approach for Twitter Data Analysis using Clustering and J48 Classification

International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Year of Publication: 2016
Ravikant Choudhary, Deepak Sain

Ravikant Choudhary and Deepak Sain. An Improved Approach for Twitter Data Analysis using Clustering and J48 Classification. International Journal of Computer Applications 156(14):35-41, December 2016. BibTeX

	author = {Ravikant Choudhary and Deepak Sain},
	title = {An Improved Approach for Twitter Data Analysis using Clustering and J48 Classification},
	journal = {International Journal of Computer Applications},
	issue_date = {December 2016},
	volume = {156},
	number = {14},
	month = {Dec},
	year = {2016},
	issn = {0975-8887},
	pages = {35-41},
	numpages = {7},
	url = {},
	doi = {10.5120/ijca2016912562},
	publisher = {Foundation of Computer Science (FCS), NY, USA},
	address = {New York, USA}


Social Media Network is one of the main source of data for various event detections. Here in this paper a new and efficient method for the Detection of Traffic in Online Social Network Data is proposed using Clustering and Classification of Data. The Planned Procedure applied here is based on SVM Supervised Learning based Clustering of Similar features of Traffic and then classify the Data using J48 Decision Tree to classify number of events performed in the Twitter Traffic. The Planned Procedure is then compared with the Existing Classification approached such as SVM and Naïve Bayes and C4.5, but the technique is more efficient in comparison.


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Online Social Media Network, J48, SVM, Naïve Bayes, Real Time Traffic, C4.5, Classification.