Proceedings ArticleDOI
Group Intimacy and Network Formation
Kibum Kim,Woo Seong Jo,Beom Jun Kim +2 more
- pp 366-370
TLDR
A growing network model in which the strength of the intimacy among members is a tunable control parameter is proposed and it is found that it takes longer time for new nodes to make strong connections when the intimacy becomes stronger.Abstract:
Recent development of information technology allows us to efficiently communicate with others, sharing common interest and finding new friends. Numerous online communities are formed and disappear, but only a few survive the competition. Even after the survival, they eventually suffer from a decline as time goes on. Formation of a small intimate group within a community is often observed, and the members of this tightly-connected group play an important role providing strong activity in the community. However, the development of such an intimate group can exhibit a dark side effect: Other members in the community may feel left out and isolated, and newcomers may have hard time to join the already established intimacy. We believe that such a development of the tightly connected group of small number of intimate members can harm the further growth of the whole community, eventually reducing the community size. In this paper, we propose a growing network model in which the strength of the intimacy among members is a tunable control parameter. We observe how the size of the giant component is affected by the strength of the intimacy and find that it takes longer time for new nodes to make strong connections when the intimacy becomes stronger. Such alienated newcomers lose their connections and are driven out of the system, reducing the size of the connected component of the network.read more
Citations
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Journal ArticleDOI
The structure of coevolving infection networks
TL;DR: A method is developed to study this dynamic equilibrium and give an analytic description of the structure of the characteristic degree distributions and other network measures and can be used to determine the steady-state topology of many other adaptive networks.
References
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Journal ArticleDOI
Emergence of Scaling in Random Networks
TL;DR: A model based on these two ingredients reproduces the observed stationary scale-free distributions, which indicates that the development of large networks is governed by robust self-organizing phenomena that go beyond the particulars of the individual systems.
Book
Networks: An Introduction
TL;DR: This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas.
Journal ArticleDOI
The large-scale organization of metabolic networks
TL;DR: In this paper, the authors present a systematic comparative mathematical analysis of the metabolic networks of 43 organisms representing all three domains of life, and show that despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.
The large-scale organization of metabolic networks
Hawoong Jeong,B. Tombor,Réka Albert,Z. N. Oltavai,Albert-László Barabási,T. Dandekar,Stefan Schuster +6 more
TL;DR: This analysis of metabolic networks of 43 organisms representing all three domains of life shows that, despite significant variation in their individual constituents and pathways, these metabolic networks have the same topological scaling properties and show striking similarities to the inherent organization of complex non-biological systems.
Journal ArticleDOI
Scientific collaboration networks. II. Shortest paths, weighted networks, and centrality
Mark Newman,Mark Newman +1 more
TL;DR: In this article, the authors constructed networks of collaboration between scientists in each of these disciplines and proposed a measure of collaboration strength based on the number of papers coauthored by pairs of scientists, and the number other scientists with whom they coauthored those papers.