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[Dbworld] Call for abstracts: SunBelt session on multiplex, multimode and multilayer networks
Matteo Magnani
2018-12-03 10:25:55 UTC
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We are happy to invite you to submit an abstract to present your work at the the session on "Advances in multiplex, multimode and multilayer networks: methods and applications" at the XXXIX Sunbelt Conference, June 18-June 23, 2019, Montréal.

Submission deadline: February 1, 2019 (23:00 EST)

Submission page: http://sunbelt2019.ca/submission/

In multilayer social networks, actors and their connections are organised into groups called layers, so that the relations between layers can be used as a part of the network analysis process. Notable types of multilayer networks that have been studied for a long time in social network analysis are multiplex and multimode networks, the former allowing the existence of multiple types of edges between the same set of actors, the latter allowing the existence of different types of actors. Multilayer networks have recently emerged as a generalisation of these approaches to deal with the complex nature of human relations.

This session will focus on recent methodological advances for the analysis of multiplex, multimode and multilayer networks. Visualisation, clustering and community detection, as well as the definition of new network measures still represent open challenges. At the same time, presentations of substantive applications are welcome.
 
More specifically, topics for this session include:

1. Developments in computational and statistical methods for multilayer networks.
2. Multilayer network measures and modelling.
3. Applications of multilayer networks.
4. New software for multilayer networks.

Sunbelt is the main conference in the social network analysis area, and is a very interdisciplinary venue. Please notice that there are no proceedings for conference presentations, differently from many venues in computer science.

At the conference there will also be (among many others) a tutorial on multiplex social network analysis using the R library "multinet".

We look forward to receiving your contributions!

Matteo Magnani, Uppsala University, Sweden
Giancarlo Ragozini, University of Napoli Federico II, Italy
Luca Rossi, IT University, Copenhagen
Maria Prosperina Vitale, University of Salerno, Italy
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