# Random Walks on Multiplex Networks

arXiv: https://arxiv.org/abs/1306.0519 · HTML: https://mlsanity.com/paper/1306.0519/

## Key facts

- Cited by 10 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 3 Jun 2013.

## Built on by (most cited first, 10 of 10)

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- [Systematic assessment of the quality of fit of the stochastic block model for empirical networks](https://mlsanity.com/paper/2201.01658/) (2022)
- [A Tensor-Based Formulation of Hetero-functional Graph Theory](https://mlsanity.com/paper/2101.07220/) (2021)
- [Thematic recommendations on knowledge graphs using multilayer networks](https://mlsanity.com/paper/2105.05733/) (2021)
- [Reconstructing Sparse Multiplex Networks with Application to Covert Networks](https://mlsanity.com/paper/2208.01739/) (2022)
- [Learning the Right Layers: a Data-Driven Layer-Aggregation Strategy for Semi-Supervised Learning on Multilayer Graphs](https://mlsanity.com/paper/2306.00152/) (2023)

## Abstract (arXiv)

Multiplex networks are receiving increasing interests because they allow to model relationships between networked agents on several layers simultaneously. In this supplementary material for the paper "Navigability of interconnected networks under random failures", we extend well-known random walks to multiplexes and we introduce a new type of walk that can exist only in multiplexes. We derive exact expressions for vertex occupation time and the coverage. Finally, we show how the efficiency in exploring the multiplex critically depends on the underlying topology of layers, the weight of their inter-connections and the strategy adopted to walk.