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相关论文: Modelling Aging Characteristics in Citation Networ…

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To account for strong aging characteristics of citation networks, we modify Google's PageRank algorithm by initially distributing random surfers exponentially with age, in favor of more recent publications. The output of this algorithm,…

物理与社会 · 物理学 2009-11-13 Dylan Walker , Huafeng Xie , Koon-Kiu Yan , Sergei Maslov

Ever since the Barab\'{a}si-Albert (BA) scale-free network has been proposed, network modeling has been studied intensively in light of the network growth and the preferential attachment (PA). However, numerous real systems are featured…

社会与信息网络 · 计算机科学 2025-11-25 Yuhan Li , Minyu Feng , Jürgen Kurths

We study the statistics of growing networks in which each link carries a weight (k_i k_j)^theta, where k_i and k_j are the node degrees at the endpoints of link ij. Network growth is governed by preferential attachment in which a…

统计力学 · 物理学 2009-11-10 E. Almaas , P. L. Krapivsky , S. Redner

We introduce a new analytical framework for modelling degree sequences in individual communities of real-world networks, e.g., citations to papers in different fields. Our work is inspired by a recent modification of the Price's model,…

物理与社会 · 物理学 2026-04-29 Łukasz Brzozowski , Marek Gagolewski , Grzegorz Siudem , Barbara Żogała-Siudem

We investigate choice-driven network growth. In this model, nodes are added one by one according to the following procedure: for each addition event a set of target nodes is selected, each according to linear preferential attachment, and a…

统计力学 · 物理学 2014-07-25 P. L. Krapivsky , S. Redner

Academic citation graphs represent citation relationships between publications across the full range of academic fields. Top cited papers typically reveal future trends in their corresponding domains which is of importance to both…

机器学习 · 计算机科学 2021-04-07 Daniel Cummings , Marcel Nassar

There has been a long history of research into the structure and evolution of mankind's scientific endeavor. However, recent progress in applying the tools of science to understand science itself has been unprecedented because only recently…

统计力学 · 物理学 2009-11-10 Katy Börner , Jeegar T. Maru , Robert L. Goldstone

We present exact results for the degree distribution in a directed network model that grows by node duplication (ND). Such models are useful in the study of the structure and growth dynamics of gene regulatory networks and scientific…

物理与社会 · 物理学 2019-08-21 Chanania Steinbock , Ofer Biham , Eytan Katzav

Many complex networks from the World-Wide-Web to biological networks are growing taking into account the heterogeneous features of the nodes. The feature of a node might be a discrete quantity such as a classification of a URL document as…

物理与社会 · 物理学 2013-05-30 Luca Ferretti , Michele Cortelezzi , Bin Yang , Giacomo Marmorini , Ginestra Bianconi

This paper presents a comprehensive analysis of the degree statistics in models for growing networks where new nodes enter one at a time and attach to one earlier node according to a stochastic rule. The models with uniform attachment,…

统计力学 · 物理学 2015-05-13 C. Godreche , H. Grandclaude , J. M. Luck

Network models with preferential attachment, where new nodes are injected into the network and form links with existing nodes proportional to their current connectivity, have been well studied for some time. Extensions have been introduced…

物理与社会 · 物理学 2013-06-26 James P. Bagrow , Dirk Brockmann

We propose a model of network growth in which the network is co-evolving together with the dynamics of a quantum mechanical system, namely a quantum walk taking place over the network. The model naturally generalizes the Barab\'{a}si-Albert…

Reciprocity characterizes the information exchange between users in a network, and some empirical studies have revealed that social networks have a high proportion of reciprocal edges. Classical directed preferential attachment (PA) models,…

物理与社会 · 物理学 2021-08-10 Tiandong Wang , Sidney I. Resnick

Reciprocity in social networks helps understand information exchange between two individuals, and indicates interaction patterns between pairs of users. A recent study indicates the reciprocity coefficient of a classical directed…

物理与社会 · 物理学 2022-01-12 Daniel Cirkovic , Tiandong Wang , Sidney Resnick

In this paper, we propose a growing random complex network model, which we call context dependent preferential attachment model (CDPAM), when the preference of a new node to get attached to old nodes is determined by the local and global…

社会与信息网络 · 计算机科学 2015-01-13 Pradumn Kumar Pandey , Bibhas Adhikari

In this paper we report first results of our study on network characteristics of a reference-based, bibliographically coupled (BC) publication network structure. We find that this network of clustered publications shows different topologies…

统计力学 · 物理学 2007-05-23 Anthony F. J. van Raan

Extensive literature demonstrates how the copying of references (links) can lead to the emergence of various structural properties (e.g., power-law degree distribution and bipartite cores) in bibliographic and other similar directed…

社会与信息网络 · 计算机科学 2019-12-30 Pradumn Kumar Pandey , Mayank Singh , Pawan Goyal , Animesh Mukherjee , Soumen Chakrabarti

Whether citations can be objectively and reliably used to measure productivity and scientific quality of articles and researchers can, and should, be vigorously questioned. However, citations are widely used to estimate the productivity of…

社会与信息网络 · 计算机科学 2026-01-26 George Chacko , Minhyuk Park , Vikram Ramavarapu , Ananth Grama , Pablo Robles-Granda , Tandy Warnow

Motivated by widely observed examples in nature, society and software, where groups of already related nodes arrive together and attach to an existing network, we consider network growth via sequential attachment of linked node groups, or…

In principle, the rules of links formation of a network model can be considered as a kind of link prediction algorithm. By revisiting the preferential attachment mechanism for generating a scale-free network, here we propose a class of…

物理与社会 · 物理学 2012-11-09 Ke Hu , Ju Xiang , Wanchun Yang , Xiaoke Xu , Yi Tang