Analyzing & Predicting social networking big data: using Network and Regression Techniques

Abstract

According to survey 2.4 billion users prefer facebook as a best platform among several social network sites. It is estimated that there are approx 4 billion people are using social network in the world. Among all social network sites, facebook is crowded, popular and best communicated platform. When large amount of data are stored in the distributed form. Social Networking Big data that has panacea role to handle large amount of data for social network. We have studied several literature regarding role of social networking big data in facebook and instagram because these are crowded platform and prove our research problem that are facing by all researchers. Although, even after being popularity of facebok regarding social network site, we all face many problems during use of social networking big data. All opportunities, issues, problems, challenges are mentioned in this paper. We also tried to explain what the major role of Machine Learning, Cloud Service Models, Security factors in cloud and social networking big data analytics. We are also expressing, why we adapt facebook and instagram algorithm? Through this paper, we are trying to show that Networkx and Regression techniques will prove to be very effective for those researchers who want to extract or predict accurate value on a dataset of social network and analyze those data. We have made a meaningful effort through this paper.