BYU

Abstract by Juan Rodriguez

Personal Infomation


Presenter's Name

Juan Rodriguez

Co-Presenters

None

Degree Level

Undergraduate

Co-Authors

None

Abstract Infomation


Department

Mathematics

Faculty Advisor

Emily Evans

Title

Centrality Measures in Large Dynamic Networks

Abstract

 

Most networks that we study or encounter on a daily basis are dynamic in the sense that relationships are constructed or destroyed and actors join or leave the network as time progresses. Most research done in network theory relates to the analysis of static graph. Given this chasm between research and reality, we chose to research large networks in their natural dynamic state. The importance of this matter underlies in the fact that understanding the evolution of dynamic networks would enable us to solve problems in urban planning, disease dissemination, and societal interactions; we would then understand population dynamics and be able to forecast structural changes. We approach this problem by analyzing the progression of centrality measures for large networks and attempt to forecast their evolution.