Analysis and evaluation of random-based message propagation models on the social networks

Abstract

Social network services (SNS), based on the complex relationships among people in real-life and virtual world, have become a major internet service for people to communicate with each other. Different social networks have different characteristics and varying levels of influence. To understand the message propagation process, the driving power behind it and its social influence, this paper presents a detailed analysis of message propagation models over the social networks by analyzing the relationships among nodes. This paper presents five proposed models which aim to analyze message propagations on social networks. We analyze the message propagation models and show how messages spread through the social networks. Furthermore, we propose a social network analysis on Hadoop platform to verify the social network characteristics. We also present a measurement study of messages collected from 900 K users on Facebook, to verify our proposed models by means of big-data Hadoop platform. We believe that our research provides valuable insights for future social network service research.