Abstract
Motivated by biological aging dynamics, we introduce a network evolution model for social interaction networks. In order to study the effect of social interactions originating from biological and sociological reasons on the topological properties of networks, we introduce the activitydependent rewiring process. From the numerical simulations, we show that the degree distribution of the obtained networks follows a power-law distribution with an exponentially decaying tail, P(k) ~ (k + c) -γ exp(-k/k 0). The obtained value of γ is in the range 2 < γ < 3, which is consistent with the values for real social networks. Moreover, we also show that the degree-degree correlation of the network is positive, which is a characteristic of social interaction networks. The possible applications of our model to real systems are also discussed.
| Original language | English |
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| Pages (from-to) | 621-624 |
| Number of pages | 4 |
| Journal | Journal of the Korean Physical Society |
| Volume | 60 |
| Issue number | 4 |
| DOIs | |
| Publication status | Published - Feb 2012 |
Bibliographical note
Funding Information:We thank Mr. H. Kim and Mr. B. Han for the computational work. This work was supported by National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MEST) (No. 2009-0073939 and No. 2010-0021586) and by the Korea Research Foundation Grant funded by the Korean Government (MOEHRD, Basic Research Promotion Fund) (KRF-2008-321-B00031). One of the authors (Yup Kim) acknowledges the support from Kyung Hee University through the requested research year 2011.
Keywords
- Complex networks
- Network evolution
- Social networks