Analysis of Social Network

Abstract

Social Networks in the last decade has achieved incredible attention. This is qualified to the reason of accessing social network sites such as Face book, Hike, Instagram and other social network sites through the internet. Most of the people are becoming attracted in and depending on the Social Network for information and opinion of other users on various issue matters. It is important to convert opinion articulated by Social Networks users to useful information using data mining techniques. This underscores the importance of data mining techniques on Social Networks. Data mining techniques are capable of managing the three prevailing research issues with Social Networks data which are mass, noise and vitality. These techniques were used in information retrieval, statistical modeling and machine learning. These techniques use steps like data pre-processing, data analysis, and data interpretation processes. This paper reviews data mining techniques currently in use on analyzing Social Network and used k-means algorithm for clustering and fuzzy classification algorithm for classifying the data. And finally predicting which network is used by most of the people.