Date of Graduation
Master of Science in Statistics and Analytics (MS)
Second Committee Member
Third Committee Member
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.
Ek, Luis Javier Jr., "Statistical Modeling of the Temporal Dynamics in a Large Scale-Citation Network" (2016). Theses and Dissertations. 1549.