{ "id": "1707.02492", "version": "v1", "published": "2017-07-08T20:24:18.000Z", "updated": "2017-07-08T20:24:18.000Z", "title": "PageRank on inhomogeneous random digraphs", "authors": [ "Jiung Lee", "Mariana Olvera-Cravioto" ], "categories": [ "math.PR" ], "abstract": "We study the typical behavior of a generalized version of Google's PageRank algorithm on a large family of inhomogeneous random digraphs. This family includes as special cases directed versions of classical models such as the Erd\\\"os-R\\'enyi model, the Chung-Lu model, the Poissonian random graph and the generalized random graph, and is suitable for modeling scale-free directed complex networks where the number of neighbors a vertex has is related to its attributes. In particular, we show that the rank of a randomly chosen node in a graph from this family converges weakly to the attracting endogenous solution to the stochastic fixed-point equation $$\\mathcal{R} \\stackrel{\\mathcal{D}}{=} \\sum_{i=1}^{\\mathcal{N}} \\mathcal{C}_i \\mathcal{R}_i + \\mathcal{Q},$$ where $(\\mathcal{N}, \\mathcal{Q}, \\{\\mathcal{C}_i\\}_{i \\geq 1})$ is a real-valued vector with $\\mathcal{N}\\in \\{0,1,2,...\\}$, the $\\{ \\mathcal{R}_i\\}$ are i.i.d.~copies of $\\mathcal{R}$, independent of $(\\mathcal{N}, \\mathcal{Q}, \\{\\mathcal{C}_i\\}_{i \\geq 1})$, with $\\{ \\mathcal{C}_i\\}$ i.i.d.~and independent of $(\\mathcal{N}, \\mathcal{Q})$; $\\stackrel{\\mathcal{D}}{=}$ denotes equality in distribution. This result can then be used to provide further evidence of the power-law behavior of PageRank on scale-free graphs.", "revisions": [ { "version": "v1", "updated": "2017-07-08T20:24:18.000Z" } ], "analyses": { "subjects": [ "05C80", "60J80", "68P20", "41A60", "37A30", "60B10" ], "keywords": [ "inhomogeneous random digraphs", "poissonian random graph", "stochastic fixed-point equation", "googles pagerank algorithm", "special cases directed versions" ], "note": { "typesetting": "TeX", "pages": 0, "language": "en", "license": "arXiv", "status": "editable" } } }