How Variability in Individual Patterns of Behavior Changes the Structural Properties of Networks

Somayeh Koohborfardhaghighi (skhaghighi@snu.ac.kr) and Jörn Altmann
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Somayeh Koohborfardhaghighi: Technology Management, Economics, and Policy Program, College of Engineering, Seoul National University

No 2014114, TEMEP Discussion Papers from Seoul National University; Technology Management, Economics, and Policy Program (TEMEP)

Abstract: Dynamic processes in complex networks have received much attention. This attention reflects the fact that dynamic processes are the main source of changes in the structural properties of complex networks (e.g., clustering coefficient and average shortest-path length). In this paper, we develop an agent-based model to capture, compare, and explain the structural changes within a growing social network with respect to individuals’ social characteristics (e.g., their activities for expanding social relations beyond their social circles). According to our simulation results, the probability increases that the network’s average shortest-path length is between 3 and 4, if most of the dynamic processes are based on random link formations. That means, in Facebook, the existing average shortest path length of 4.7 can even shrink to smaller values. Another result is that, if the node increase is larger than the link increase when the network is formed, the probability increases that the average shortest-path length is between 4 and 8.

Keywords: Network Properties; Network Growth Models; Small World Theory; Network Science; Simulation; Clustering Coefficient; Complex Networks. (search for similar items in EconPapers)
JEL-codes: C02 C15 C6 D85 (search for similar items in EconPapers)
Pages: 18 pages
Date: 2014-06, Revised 2014-06
New Economics Papers: this item is included in nep-cmp, nep-hme, nep-net and nep-soc
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Published in International Conference on Active Media Technology at Web Intelligence Congress (WIC 2014).

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Persistent link: https://EconPapers.repec.org/RePEc:snv:dp2009:2014114

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