2012/03/27 by Ryan A. Rossi, David F. Gleich, Rossi, Ryan A. +1 · 1 citation
Computer Science · Mathematics · Physics and Astronomy · #Adaptation (eye) #Complex Network Analysis Techniques #Computer science #Dynamical Systems (math.DS) #FOS: Computer and information sciences #FOS: Mathematics #FOS: Physical sciences #G.1.10 #G.2.2 #Graph #H.2.8 #Information Retrieval (cs.IR) #Machine Learning (stat.ML) #Node (physics) #Opinion Dynamics and Social Influence #PageRank #Peer-to-Peer Network Technologies #Physics and Society (physics.soc-ph) #Quantum entanglement #Social and Information Networks (cs.SI) #Teleportation #Theoretical computer science #cs.IR #cs.SI #math.DS #physics.soc-ph #stat.ML
paper · pdf · doi:10.48550/arxiv.1203.6098
published in arXiv (Cornell University) (Cornell University) · WAW 2012
arxiv created 2012/03/27 · openalex publication_date 2012/03/27 · arxiv updated 2012/03/29 · openalex created_date 2025/10/10 · openalex updated_date 2026/08/08
The importance of nodes in a network constantly fluctuates based on changes in the network structure as well as changes in external interest. We propose an evolving teleportation adaptation of the PageRank method to capture how changes in external interest influence the importance of a node. This framework seamlessly generalizes PageRank because the importance of a node will converge to the PageRank values if the external influence stops changing. We demonstrate the effectiveness of the evolving teleportation on the Wikipedia graph and the Twitter social network. The external interest is given by the number of hourly visitors to each page and the number of monthly tweets for each user.