Date of Graduation

5-2016

Document Type

Thesis

Degree Name

Master of Science in Statistics and Analytics (MS)

Degree Level

Graduate

Department

Statistics and Analytics

Advisor/Mentor

Qingyang Zhang

Committee Member

Giovanni Petris

Second Committee Member

Avishek Chakraborty

Third Committee Member

Mark Arnold

Keywords

Pure sciences, Ba model, Cauchy distribution, Dirichlet, Large-citation network

Abstract

Citation Networks of papers are vast networks that grow over time. The manner or the form a citation network grows is not entirely a random process, but a preferential attachment relationship; highly cited papers are more likely to be cited by newly published papers. The result is a network whose degree distribution follows a power law. This growth of citation network of papers will be modeled with a negative binomial regression coupled with logistic growth and/or Cauchy distribution curve. Then a Barabasi-Albert model, based on the negative binomial models, and a combination of the Dirichlet distribution and multinomial will be utilized to simulate a network that follows preferential attachments between newly added nodes and existing nodes.

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