| Summary: | 博士 === 國立中山大學 === 資訊工程學系研究所 === 104 === Social network services (SNS) have become a major internet service for people to communicate with each other. It is full of complex relationships among people in the real-life and virtual world. 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 four proposed models which aim to analyze message propagation on social networks. We analyze the message propagation models and show how messages spread through the social networks. We also analyze and describe the significance and influence of clustering parameters in the model on the social clusters. Furthermore, we propose an social network analysis on Hadoop platform and implement a prototype to verify the social network characteristics. Hadoop platform can process massive data in a parallel manner on a large cluster built by commodity hardware. 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.
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