Stylized facts in social networks: Community-based static modeling

Research output: Contribution to journalArticleScientificpeer-review

Researchers

Research units

  • Asia Pacific Center for Theoretical Physics
  • Pohang University of Science and Technology
  • RIKEN
  • Budapest University of Technology and Economics
  • Central European University

Abstract

The past analyses of datasets of social networks have enabled us to make empirical findings of a number of aspects of human society, which are commonly featured as stylized facts of social networks, such as broad distributions of network quantities, existence of communities, assortative mixing, and intensity-topology correlations. Since the understanding of the structure of these complex social networks is far from complete, for deeper insight into human society more comprehensive datasets and modeling of the stylized facts are needed. Although the existing dynamical and static models can generate some stylized facts, here we take an alternative approach by devising a community-based static model with heterogeneous community sizes and larger communities having smaller link density and weight. With these few assumptions we are able to generate realistic social networks that show most stylized facts for a wide range of parameters, as demonstrated numerically and analytically. Since our community-based static model is simple to implement and easily scalable, it can be used as a reference system, benchmark, or testbed for further applications.

Details

Original languageEnglish
Pages (from-to)23-39
Number of pages17
JournalPhysica A: Statistical Mechanics and its Applications
Volume500
Publication statusPublished - 15 Jun 2018
MoE publication typeA1 Journal article-refereed

ID: 18143917