• V.Uday Kumar
• S.Balaji

The main aim of this project is finding the repeated activities in a social network. The different post that are continuously posted by a user in the twitter. The text information arriving continuously arriving over the time in the form of text stream are predicted and clustered for analysis. This project will track what type of information that continuously arriving in social media and the people interest. All the operations are going to be performed on the twitter dataset. The dataset which consisting of Twitter users and their tweets.This model is proposed to analyse the contagion dynamics that emerge in networks when repeated activation is allowed, that is, when actors can engage recurrently in a collective effort. In this project, the k-means clustering algorithm is used for clustering the users based on their interest and Naïve Bayes classification algorithm is used for classifying the users. And also in this project we can track the interest of the particular result. This project will increase the accuracy of the overall prediction results.

Clustering Naïve Bayes classification algorithm etc.

"Enhancement the Performance of the Tracking and Clustering in Tweets Data Stream using Naïve Bayes Classification Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.8, Issue 1, page no.496-501, January-2021, Available :http://www.jetir.org/papers/JETIR2101066.pdf

"Enhancement the Performance of the Tracking and Clustering in Tweets Data Stream using Naïve Bayes Classification Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.8, Issue 1, page no. pp496-501, January-2021, Available at : http://www.jetir.org/papers/JETIR2101066.pdf