To Study and Analyse Human Behaviours on Social Networks

Recently, the scope of the digital world in increased in a way that a number of smart objects are connecting in a huge quantity. It is due to the exploitation of low-cost internet extensions, air-interface, and revolution in miniaturization. Hence, it results in decreasing the cost of a smart device. The growing gap between users and the Big Data analytics requires innovative tools that address the challenges faced by big data volume, variety, and velocity. Therefore, it becomes computationally inefficient to analyse such massive volume of data. Therefore, keeping in view the aforementioned needs, there is a requirement for a system that can efficiently analyse a stream of Big Data within their requirements. Hence, this paper presents a system architecture that integrates social network with the technical network. We derive a novel notion of 'Socio-Cyber Network', where a friendship is made based on the geo-location information of the user, where trust index is used based on graphs theory. To check the efficiency of the proposed algorithms exploited in the proposed system architecture, we have implemented our proposed system using Hadoop and MapReduce. Moreover, the system is evaluated in terms of efficiency by considering the system throughput and processing time.