Call: "Multi-layer and feature-rich networks" (EUSN 2022)

Submissions and info: https://eusn2022.org/ (you can select the track when registering a submission)

Deadline: May 8, 2022 (AoE)

Description: In recent years it has become more and more frequent to use network
models going beyond simple directed/undirected and weighted/unweighted
networks, to capture the complexity of old and new fields of
application of network analysis. Multilayer networks are an example of
such models, extending graphs with the concept of layer, that allows
us to represent a multitude of scenarios from the different types of
ties we find in a multiplex network, to different types of actors, to
different temporal snapshots of the relations between the same group
of actors. Multilayer network models can themselves be enriched with
additional features, such as attributes and edge probabilities, with
the aim of describing real phenomena in more detail.

Multilayer and feature-rich networks allow us to introduce new
research questions (and corresponding social network analysis measures
and methods). For example, instead of asking how central an actor is,
we can focus on the role of the different layers in determining the
centrality of the actors. Second, existing social network analysis
concepts do not always have a clear corresponding extension in complex
networks. For example, it is still unclear how communities spanning
multiple layers should look like, or how different features should
contribute to the definition of communities, or how to effectively
visualise multilayer and feature-rich networks, e.g. layers, features
or modes, in the same sociogram. In addition, multilayer networks
allow to use multiple types of layers (e.g., in temporal multiplex
networks), which requires the joint application of methods developed
for simpler models (e.g., only temporal, or only multiplex).

Topics: This session focuses on recent advances in the analysis of multilayer

and feature-rich networks, either in terms of new research questions,
or new methods, or new applications. More specifically, topics for
this session include but are not limited to:

1. New models for multilayer and feature-rich networks, or comparison
of alternative models;
2. Measures for multilayer and feature-rich network;
3. Community discovery in multilayer and feature-rich networks;
4. Multilayer and feature-rich network embedding;
5. Visualisation of multilayer and feature-rich network;
6. Multilayer and feature-rich network simplification (e.g., sampling,
filtering, flattening, projections);
7. Applications;
8. Software.