Mikko Kivelä

Publications36
h-index14
Citations3,643
Highly Influential Citations155
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Multilayer networks
TLDR
We discuss the history of multilayer networks (and related concepts) and review the exploding body of work on such networks. Expand
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Small But Slow World: How Network Topology and Burstiness Slow Down Spreading
TLDR
We follow the time evolution of information propagation through communication networks by using empirical data on contact sequences and the susceptible-infected model. Expand
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Characterizing the Community Structure of Complex Networks
TLDR
We present a systematic empirical analysis of the statistical properties of communities in large information, communication, technological, biological, and social networks. Expand
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Generalizations of the clustering coefficient to weighted complex networks.
The recent high level of interest in weighted complex networks gives rise to a need to develop new measures and to generalize existing ones to take the weights of links into account. Here we focus on… Expand
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Sequential algorithm for fast clique percolation.
In complex network research clique percolation, introduced by Palla, Derényi, and Vicsek [Nature (London) 435, 814 (2005)], is a deterministic community detection method which allows for overlapping… Expand
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A comparative study of social network models: Network evolution models and nodal attribute models
TLDR
This paper reviews, classifies and compares recent models for social networks that have mainly been published within the physics-oriented complex networks literature, with the aim of determining which models produce the most realistic network structure with respect to degree distributions, assortativity, clustering spectra, geodesic path distributions, and community structure (subgroups with dense internal connections). Expand
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EDENetworks: A user‐friendly software to build and analyse networks in biogeography, ecology and population genetics
The recent application of graph‐based network theory analysis to biogeography, community ecology and population genetics has created a need for user‐friendly software, which would allow a wider… Expand
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Multiscale Analysis of Spreading in a Large Communication Network
TLDR
In temporal networks, both the topology of the underlying network and the timings of interaction events can be crucial in determining how a dynamic process mediated by the network unfolds. Expand
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Using explosive percolation in analysis of real-world networks.
TLDR
We apply a variant of the explosive percolation procedure to large real-world networks and show with finite-size scaling that the university class, ordinary or explosive, depends on the structural properties of the network, as well as the number of unoccupied links considered for comparison in our procedure. Expand
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Randomized reference models for temporal networks
TLDR
We propose a unified framework for classifying and understanding microcanonical RRMs (MRRMs) that sample networks with uniform probability. Expand
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