Uncovering collective listening habits and music genres in bipartite networks.

@article{Lambiotte2005UncoveringCL,
  title={Uncovering collective listening habits and music genres in bipartite networks.},
  author={Renaud Lambiotte and Marcel Ausloos},
  journal={Physical review. E, Statistical, nonlinear, and soft matter physics},
  year={2005},
  volume={72 6 Pt 2},
  pages={
          066107
        }
}
  • R. Lambiotte, M. Ausloos
  • Published 31 August 2005
  • Computer Science
  • Physical review. E, Statistical, nonlinear, and soft matter physics
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References

SHOWING 1-10 OF 21 REFERENCES
The do re mi's of everyday life: the structure and personality correlates of music preferences.
TLDR
The data indicated that people consider music an important aspect of their lives and listening to music an activity they engaged in frequently, and the links between music preferences and personality were related to a wide array of personality dimensions.
Statistical mechanics of complex networks
TLDR
A simple model based on these two principles was able to reproduce the power-law degree distribution of real networks, indicating a heterogeneous topology in which the majority of the nodes have a small degree, but there is a significant fraction of highly connected nodes that play an important role in the connectivity of the network.
Identity and Search in Social Networks
TLDR
A model is presented that offers an explanation of social network searchability in terms of recognizable personal identities: sets of characteristics measured along a number of social dimensions that may be applicable to many network search problems.
Stochastic resonance in a model of opinion formation on small-world networks
Abstract:We analyze the phenomenon of stochastic resonance in an Ising-like system on a small-world network. The system, which is subject to the combined action of noise and an external modulation,
Minority opinion spreading in random geometry
Abstract:The dynamics of spreading of the minority opinion in public debates (a reform proposal, a behavior change, a military retaliation) is studied using a diffusion reaction model. People move by
Class of correlated random networks with hidden variables.
TLDR
The general model is extended to describe a practical algorithm to generate random networks with an a priori specified correlation structure and an extension is presented, to map nonequilibrium growing networks to networks with hidden variables that represent the time at which each vertex was introduced in the system.
Average path length in random networks.
TLDR
The result for 2<alpha<3 shows that structural properties of asymptotic scale-free networks including numerous examples of real-world systems are even more intriguing than ultra-small world behavior noticed in pure scale- free structures and for large system sizes N-->infinity there is a saturation effect for the average path length.
Listening in: practices surrounding iTunes music sharing
TLDR
This paper describes adoption, critical mass, and privacy; impression management and access control; the musical impressions of others that are created as a result of music sharing; the ways in which participants attempted to make sense of the dynamic system; and implications of the overlaid technical, musical, and corporate topologies.
Potts model on complex networks
Abstract.We consider the general p-state Potts model on random networks with a given degree distribution (random Bethe lattices). We find the effect of the suppression of a first order phase
...
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