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Impact of snowball sampling ratios on network characteristics estimation: A case study of Cyworld
곽해운(Haewoon Kwak),한승엽(Seungyeop Han),안용열(Yong-Yeol Ahn),문수복(Sue Moon),정하웅(Hawoong Jeong) 한국정보과학회 2006 한국정보과학회 학술발표논문집 Vol.33 No.2D
Today's social networking services have tens of millions of users, and are growing fast. Their sheer size poses a significant challenge in capturing and analyzing their topological characteristics. Snowball sampling is a popular method to crawl and sample network topologies, but requires a high sampling ratio for accurate estimation of certain metrics. In this work, we evaluate how close topological characteristics of snowball sampled networks are to the complete network. Instead of using a synthetically generated topology, we use the complete topology of Cyworld ilchon network. The goal of this work is to determine sampling ratios for accurate estimation of key topological characteristics, such as the degree distribution, the degree correlation, the assortativity, and the clustering coefficient.