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
Zhang, Qingyang
Committee Member
Petris, Giovanni G.
Second Committee Member
Chakraborty, Avishek A.
Third Committee Member
Arnold, Mark E.
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.
Citation
Ek, L. J. (2016). Statistical Modeling of the Temporal Dynamics in a Large Scale-Citation Network. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/1549
