Analysis of Social Networking Sites Using K- Mean Clustering Algorithm

Abstract

Clustering is one of the very important technique used for classification of large dataset and widely applied to many applications including analysis of social networking sites, aircraft accidental, company performance etc. In recent days, Communication, advertising through social networking sites are most popular and interactive strategy among the users. This research attempts to find the large scale measurement study and analysis, effectiveness of communication strategy, analyzing the information about the usage, people’s interest in social network sites in promoting and advertising their brand in social networking sites. The significance of the proposed work is determined with the help of various surveys, and from people who use these sites. Further a more specific pre-processing method is applied to clean data and perform the clustering method to generate patterns that will be work as heuristics for designing more effective social networking sites.

Real-Time Surveillance System for Detection of Social Distancing

“…After this modification the resulting score that will be obtained will have the same relative proportions and can be still used efficaciously inside machine learning. (Kumar & Thakur, 2019, 2021a, 2021b) (D. Rajput, Thakur, Thakur, & Sahu, 2012 algorithm for finding the most similar examples:…”