Imparting Social Connectivity Issues and Social Networking Exploration via Evolutionary Algorithms and Big Data Analysis

Abstract

This research focuses on the review and analytical survey of social connectivity with the concepts of Big Data analysis. These issues such as cluster analysis, personalized search, anomaly detection, community detection, load balancing, selection, structural balancing and cut space searching related to social networking are broadly discussed which can further improved via machine learning techniques like evolutionary algorithm, swarm optimization and genetic algorithms. Properties such as graph triadic closure etc enhances the behavior of social networking issue when applied to datasets of various social networking platforms