Journal article

Emergence of scale-free leadership structure in social recommender systems

  • Zhou, Tao Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland - Department of Modern Physics, University of Science and Technology of China, Hefei, China
  • Medo, Matúš Department of Physics, University of Fribourg, Switzerland
  • Cimini, Giulio Department of Physics, University of Fribourg, Switzerland
  • Zhang, Zi-Ke Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland
  • Zhang, Yi-Cheng Web Sciences Center, University of Electronic Science and Technology of China, Chengdu, China - Department of Physics, University of Fribourg, Switzerland
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    27.07.2011
Published in:
  • PLoS ONE. - 2011, vol. 6, no. 7, p. e20648
English The study of the organization of social networks is important for the understanding of opinion formation, rumor spreading, and the emergence of trends and fashion. This paper reports empirical analysis of networks extracted from four leading sites with social functionality (Delicious, Flickr, Twitter and YouTube) and shows that they all display a scale-free leadership structure. To reproduce this feature, we propose an adaptive network model driven by social recommending. Artificial agent-based simulations of this model highlight a “good get richer” mechanism where users with broad interests and good judgments are likely to become popular leaders for the others. Simulations also indicate that the studied social recommendation mechanism can gradually improve the user experience by adapting to tastes of its users. Finally we outline implications for real online resource-sharing systems.
Faculty
Faculté des sciences
Department
Physique
Language
  • English
Classification
Physics
License
License undefined
Identifiers
Persistent URL
https://folia.unifr.ch/unifr/documents/302158
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