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Social Network Analysis: Statistical Model, Community Detection and Friend Recommendation

  • Author(s): Yu, Xiaolu
  • Advisor(s): Zhou, Qing
  • et al.
Abstract

In recent years, Social Network Service (SNS) is a novel, popular way to make friends and

convey information online. Therefore, the analysis of network data has attracted a lot of

attention. It is an area that is rapidly growing, both with Statistics and Computer Science.

This paper rst provides a summary of statistical methods used in network data analysis,

including basic denitions, measurements, and descriptive statistics. We then introduce the

Exponential Random Graph Model to t network data. Secondly, we dig into a more specic

area of network analysis: Community Detection. We discuss two dierent methods to explore

the community stucture, one is Louvain algorithm and the other is Mixed Membership

Stochastic Blockmodels. After that, we combine the community identication with a two-

stage user similarity algorithm to build a friend recommendation method. In the empirical

study section, we apply this method to a real-world dataset and evaluate its performace

through specic measurements.

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