fastnet: An R Package for Fast Simulation and Analysis of Large-Scale Social Networks

被引：1

作者：

Dong, Xu ^{[1
]}

Castro, Luis ^{[2
]}

Shaikh, Nazrul ^{[3
]}

机构：

[1] Tamr Inc, Cambridge, MA USA

[2] World Bank, 1818 H St NW, Washington, DC 20433 USA

[3] Cecareus Inc, Coral Gables, FL 33134 USA

来源：

JOURNAL OF STATISTICAL SOFTWARE | 2020年 / 96卷 / 07期

关键词：

social network analysis; network simulation; network metrics; multi-core processing; sampling; DYNAMICS;

D O I：

10.18637/jss.v096.i07

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Traditional tools and software for social network analysis are seldom scalable and/or fast. This paper provides an overview of an R package called fastnet, a tool for scaling and speeding up the simulation and analysis of large-scale social networks. fastnet uses multi-core processing and sub-graph sampling algorithms to achieve the desired scale-up and speed-up. Simple examples, usages, and comparisons of scale-up and speed-up as compared to other R packages, i.e., igraph and statnet, are presented.

引用

页码：1 / 23

页数：23

共 50 条

[1] FastNet: Fast and Accurate Statistical Inference of Phylogenetic Networks Using Large-Scale Genomic Sequence Data
Hejase, Hussein A.
VandePol, Natalie
Bonito, Gregory M.
Liu, Kevin J.
[J]. COMPARATIVE GENOMICS (RECOMB-CG 2018), 2018, 11183 : 242 - 259
[2] Social Influence Analysis in Large-scale Networks
Tang, Jie
Sun, Jimeng
Wang, Chi
Yang, Zi
[J]. KDD-09: 15TH ACM SIGKDD CONFERENCE ON KNOWLEDGE DISCOVERY AND DATA MINING, 2009, : 807 - 815
[3] Analysis of large-scale social and information networks
Kleinberg, Jon
[J]. PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY A-MATHEMATICAL PHYSICAL AND ENGINEERING SCIENCES, 2013, 371 (1987):
[4] Fast Representative Sampling in Large-Scale Online Social Networks
Cai, Guangren
Lu, Gang
Guo, Junxia
Ling, Cheng
Li, Ruiqi
[J]. IEEE ACCESS, 2020, 8 : 77106 - 77119
[5] Analysis, simulation and measurement in large-scale packet networks
Mondragon, R.
Moore, A.
Pitts, J.
Schormans, J.
[J]. IET COMMUNICATIONS, 2009, 3 (06) : 887 - 905
[6] Analysis of influence maximization in large-Scale social networks
Hu, Jie
Meng, Kun
Chen, Xiaomin
Lin, Chuang
Huang, Jiwei
[J]. Performance Evaluation Review, 2014, 41 (04): : 78 - 81
[7] Large-scale analysis of grooming in modern social networks
Lykousas, Nikolaos
Patsakis, Constantinos
[J]. EXPERT SYSTEMS WITH APPLICATIONS, 2021, 176
[8] Fast Overlapping Communities Detection Algorithms for Large-Scale Social Networks
Li, Zheng-Lian
Ji, Li-Xin
Huang, Rui-Yang
Lan, Ju-Long
[J]. Tien Tzu Hsueh Pao/Acta Electronica Sinica, 2019, 47 (02): : 257 - 265
[9] SILGGM: An extensive R package for efficient statistical inference in large-scale gene networks
Zhang, Rong
Ren, Zhao
Chen, Wei
[J]. PLOS COMPUTATIONAL BIOLOGY, 2018, 14 (08)
[10] Learning Large-Scale Bayesian Networks with the sparsebn Package
Aragam, Bryon
Gu, Jiaying
Zhou, Qing
[J]. JOURNAL OF STATISTICAL SOFTWARE, 2019, 91 (11): : 1 - 38

← 1 2 3 4 5 →