Random walks and diffusion on networks

Naoki Masuda*, Mason A. Porter, Renaud Lambiotte

*この研究の対応する著者

研究成果: Review article査読

246 被引用数 (Scopus)

抄録

Random walks are ubiquitous in the sciences, and they are interesting from both theoretical and practical perspectives. They are one of the most fundamental types of stochastic processes; can be used to model numerous phenomena, including diffusion, interactions, and opinions among humans and animals; and can be used to extract information about important entities or dense groups of entities in a network. Random walks have been studied for many decades on both regular lattices and (especially in the last couple of decades) on networks with a variety of structures. In the present article, we survey the theory and applications of random walks on networks, restricting ourselves to simple cases of single and non-adaptive random walkers. We distinguish three main types of random walks: discrete-time random walks, node-centric continuous-time random walks, and edge-centric continuous-time random walks. We first briefly survey random walks on a line, and then we consider random walks on various types of networks. We extensively discuss applications of random walks, including ranking of nodes (e.g., PageRank), community detection, respondent-driven sampling, and opinion models such as voter models.

本文言語English
ページ(範囲)1-58
ページ数58
ジャーナルPhysics Reports
716-717
DOI
出版ステータスPublished - 2017 11 22
外部発表はい

ASJC Scopus subject areas

  • 物理学および天文学(全般)

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