The friendship paradox for sparse random graphs

被引:0
作者
Hazra, Rajat Subhra [1 ]
den Hollander, Frank [1 ]
Parvaneh, Azadeh [1 ]
机构
[1] Leiden Univ, Math Inst, Einsteinweg 55, NL-2333 CC Leiden, Netherlands
关键词
Sparse random graphs; Local convergence; Friendship bias;
D O I
10.1007/s00440-025-01365-w
中图分类号
O21 [概率论与数理统计]; C8 [统计学];
学科分类号
020208 ; 070103 ; 0714 ;
摘要
Let Gn\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_n$$\end{document} be an undirected finite graph on n is an element of N\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$n\in {\mathbb {N}}$$\end{document} vertices labelled by [n]={1,& mldr;,n}\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$[n] = \{1,\ldots ,n\}$$\end{document}. For i is an element of[n]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$i \in [n]$$\end{document}, let Delta i,n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta _{i,n}$$\end{document} be the friendship bias of vertex i, defined as the difference between the average degree of the neighbours of vertex i and the degree of vertex i itself when i is not isolated, and zero when i is isolated. Let mu n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu _n$$\end{document} denote the friendship-bias empirical distribution, i.e., the measure that puts mass 1n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\frac{1}{n}$$\end{document} at each Delta i,n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\Delta _{i,n}$$\end{document}, i is an element of[n]\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$i \in [n]$$\end{document}. The friendship paradox says that integral Rx mu n(dx)>= 0\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\int _{\mathbb {R}}x\mu _n(\textrm{d}x) \ge 0$$\end{document}, with equality if and only if in each connected component of Gn\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$G_n$$\end{document} all the degrees are the same. We show that if (Gn)n is an element of N\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$(G_n)_{n\in {\mathbb {N}}}$$\end{document} is a sequence of sparse random graphs that converges to a rooted random tree in the sense of convergence locally in probability, then mu n\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu _n$$\end{document} converges weakly to a limiting measure mu\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document} that is expressible in terms of the law of the rooted random tree. We study mu\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document} for four classes of sparse random graphs: the homogeneous Erd & odblac;s-R & eacute;nyi random graph, the inhomogeneous Erd & odblac;s-R & eacute;nyi random graph, the configuration model and the preferential attachment model. In particular, we compute the first two moments of mu\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document}, identify the right tail of mu\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu $$\end{document}, and argue that mu([0,infinity))>= 12\documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mu ([0,\infty ))\ge \tfrac{1}{2}$$\end{document}, a property we refer to as friendship paradox significance.
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相关论文
共 16 条
[1]   ASYMPTOTIC BEHAVIOR AND DISTRIBUTIONAL LIMITS OF PREFERENTIAL ATTACHMENT GRAPHS [J].
Berger, Noam ;
Borgs, Christian ;
Chayes, Jennifer T. ;
Saberi, Amin .
ANNALS OF PROBABILITY, 2014, 42 (01) :1-40
[2]   The friendship paradox in real and model networks [J].
Cantwell, George T. ;
Kirkley, Alec ;
Newman, M. E. J. .
JOURNAL OF COMPLEX NETWORKS, 2021, 9 (02)
[3]  
Cao Y., 2016, Math. Sci, V41, P61
[4]   The collective dynamics of smoking in a large social network [J].
Christakis, Nicholas A. ;
Fowler, James H. .
NEW ENGLAND JOURNAL OF MEDICINE, 2008, 358 (21) :2249-2258
[5]   Generalized friendship paradox in complex networks: The case of scientific collaboration [J].
Eom, Young-Ho ;
Jo, Hang-Hyun .
SCIENTIFIC REPORTS, 2014, 4
[6]   WHY YOUR FRIENDS HAVE MORE FRIENDS THAN YOU DO [J].
FELD, SL .
AMERICAN JOURNAL OF SOCIOLOGY, 1991, 96 (06) :1464-1477
[7]   LOCAL WEAK CONVERGENCE FOR PAGERANK [J].
Garavaglia, Alessandro ;
van der Hofstad, Remco ;
Litvak, Nelly .
ANNALS OF APPLIED PROBABILITY, 2020, 30 (01) :40-79
[8]  
Hazra RS, 2025, Arxiv, DOI arXiv:2312.15105
[9]  
Hodas NO., 2013, PROC 7 INT AAAI C WE, P225
[10]  
Hofstad R., 2016, Cambridge Series in Statistical and Probabilistic Mathematics, V43, P115, DOI 10.1017/9781316779422