Incorporating the Concept of Distance into PageRank's Notion of Teleportation

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Centrality measures are a valuable tool for analysing complex networks because they help us to identify the most important or central nodes in a network. One of the most popular measures of centrality is PageRank which, despite being originally introduced for ranking web pages, has found widespread use in applications far beyond the web due to its simplicity and generality. However, in many real-world networks, the notion of teleportation is counterintuitive because it implies that whatever is moving around the network will jump or 'teleport' directly from one node to any other, without considering how far apart the nodes are. Therefore, the focus of this thesis is to incorporate the concept of distance into the notion of teleportation, which is accomplished by drawing upon recent advances in non-local random walks. First, an existing PageRank-based centrality measure is extended to improve its suitability for urban street networks. Then, a general measure of PageRank centrality is proposed which can be tailored for various real-world networks and applications. To evaluate the proposed measures, experiments on a variety of real-world spatial and social networks are performed. Finally, to improve our understanding of distance-based teleportation in real-world networks, an analysis of the effect of the damping factor on the rating and ranking of nodes is provided.
Complex Networks, Centrality Measures
Bowater, D. W. (2024). Incorporating the concept of distance into PageRank's notion of teleportation (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from