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Invited Talk: Matteo Magnani, Multilayer networks meet databases: from property graphs to online information networks
December 5, 2019 @ 12:00 - 13:00
Abstract:
The analysis of complex online information requires the availability of rich data representation models and data analysis algorithms, for example multilayer networks and multilayer network clustering methods. At the same time, data analysis processes often require the ability to store raw data not yet prepared to perform a specific type of analysis, the possibility to enforce constraints guaranteeing some degree of data quality, and the capability to efficiently manipulate (or query) the raw data. This is for example important when performing interactive and visual data analysis, where several data dimensions, data subsets and aggregations have to be computed dynamically to explore different views over the data. In this work I present an extension of the multilayer network model providing database functionality on top of the idea of using the concept of layer to unify several types of graph-based models. This extension is based on the concepts of attributed vertex cube and attributed edge cube. I will conclude the presentation showing how to express a process to identify online conversations about specific topics in social media as a combination of cubes and cube operators.
Bio:
Matteo Magnani is an associate professor (“docent”) at Uppsala University, where he coordinates the Uppsala Information Laboratory (http://infolab.it.uu.se) and a new Master’s program in Data Science. Since 2011 he has developed and applied analysis methods for multilayer social networks in the context of national and European projects (FIRB and H2020 funding schemes). His results are described in his book “Multilayer Social Networks”, Cambridge University Press (2016), in several peer-reviewed publications, and implemented in the R multinet library (https://CRAN.R-project.org/package=multinet). He is also the recipient of a STINT initiation grant with TokyoTech on the topic of clustering temporal networks and of a NOS-HS grant for the establishment of a Nordic network on online disinformation. He has received the title of “Excellent teacher” (2016) and the UTN pedagogical prize (2013).