Modelling Trend Progression Through an Extension of the Polya Urn Process

M.C. ten Thij, Sandjai Bhulai

Research output: Chapter in Book / Report / Conference proceedingConference contributionAcademicpeer-review


Knowing how and when trends are formed is a frequently visited research goal. In our work, we focus on the progression of trends through (social) networks. We use a random graph (RG) model to mimic the progression of a trend through the network. The context of the trend is not included in our model. We show that every state of the RG model maps to a state of the Polya process. We find that the limit of the component size distribution of the RG model shows power-law behaviour. These results are also supported by simulations.
Original languageEnglish
Title of host publicationAdvances in Network Science
Subtitle of host publication12th International Conference and School, NetSci-X 2016, Wroclaw, Poland, January 11-13, 2016, Proceedings
EditorsA. Wierzbicki, U. Brandes, F. Schweitzer, D. Pedreschi
ISBN (Print)9783319283609
Publication statusPublished - 13 Nov 2016
Event12th International Conference and School of Network Science -
Duration: 11 Jan 201613 Jan 2016


Conference12th International Conference and School of Network Science
Abbreviated titleNetSci-X 2016

Cite this