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 900K 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.

Introduction

Recently, the rapid development and advancement of social network service (SNS) has made it possible to connect people who share the same interests and activities across political, economic, and geographic borders. Social network services have become a major internet service for people to communicate with each other. The current social network services generally operate based on the Six Degrees of Separation [1], which suggests that two random people are able to connect by a chain of six acquaintances on average, and aims to help users expand their personal networks through friends and connections. The mathematical analyses of the social network services revealed that most of the social network data and structures are too large and complex to be transformed into strict mathematical description. Therefore, computer simulations or big data analyses has become an accredited scientific verification, but how to collect useful information is a topic worth discussing. Nowadays, many researchers are interested in how to discover the rule or structure behind the complex social networks. In this paper, we present five proposed models to analyze message propagation on social networks. We analyze the message propagation models and show how messages spread through the social network.