Degree correlations in signed social networks

@article{Ciotti2014DegreeCI,
  title={Degree correlations in signed social networks},
  author={Valerio Ciotti and Ginestra Bianconi and Andrea Capocci and Francesca Colaiori and Pietro Panzarasa},
  journal={ArXiv},
  year={2014},
  volume={abs/1412.1024}
}
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21 Citations
Highly Influential Citations
2
Background Citations
5
Methods Citations
1
Results Citations
1

21 Citations

Citation Type

Citation Type

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Multilayer network decoding versatility and trust
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A massive time-varying social data drawn from the largest film industry of the world under multilayer network framework is analyzed to evaluate the versatility of actors, which turns out to be an intrinsic property of lead actors.
How to estimate the signs' configuration in the directed signed social networks?
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A physical pathway to understand individual's labeling behavior in signed social networks
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The present study encompasses the multilayer network analysis of Bollywood, the largest film industry of the world, comprising of a massive time-varying social data and indicates the gradual restoration of cooperation in the recent dataset.
Reciprocity-induced bias in digital reputation
TLDR
Evidence is presented of a network effect which biases the digital reputations of the users of P2P networks, and that the least active users are predominantly responsible for such reciprocity-induced bias, and this fact can be exploited to suppress the bias itself.
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