Network seminar: new season: 3rd November 2022

[Liubov]

Dear all,

We are happy to invite you to the first network seminar (Paris/LPI) this season. The talk will be given by Eszter Bokanyi on 3rd November at 5pm CET www.popnet.io https://www.popnet.io/team/eszter-bokanyi/

Register to get a ZOOM link to the network seminar on 3rd November
https://forms.gle/w6o1myWBQBe9Ms1k7

Event page is here
https://twitter.com/luyibov/status/1585805485042982912

The anatomy of a population-scale social network
Common large-scale approaches to inferring social structure make use of digital traces such as online social networks or mobile communication data. However, these networks are often agnostic of node and edge representativity and type. This talk investigates the structure of a social network sourced from administrative registers for an entire population based on family, household, work, school, and next-door neighbor relations, alongside rich demographic node attributes. We revisit three of the most common concepts in social network analysis: degree, closure and distance. We find that observed degrees are the result of a combination of degree distributions in various layers, disqualifying common explanatory mechanisms such as preferential attachment. Low node-to-node distances are realized through particular edge types that shortcut paths in already clustered areas. Measuring closure across layers shows how we can realistically capture the extent to which people have closed or open network opportunity structures. Finally, we highlight how people's network structure varies greatly along demographic axes such as age, income and level of education. This shows that understanding of both the type of edge and the part of the population that is considered is of great importance. Therefore, leveraging register data to capture the social structure of a complete population is one of the most fruitful ways forward to obtain actionable insights and ultimately evidence-based policies.


Bio of speaker

Eszter Bokányi is a research postdoc in the POPNET project investigating a population-scale social network of the Netherlands.

She has a background in physics, and graduated with a PhD from statistical physics at Eötvös Loránd University in Budapest. The topic of her thesis was already rather connected to computational social science, having investigated a huge database of geolocated Twitter messages.

Nowadays, she is still mostly interested in spatial social networks and their connection to human mobility, as well as dynamical phenomena.

Have a good weekend!

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Bests,

Liubov

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On behalf of organisation team,

Chakresh, Robbie, Marc, Rathin, Liuba

[Gijs van den Dool]

Hi Liubov, 

Very interesting topic, I will have to give it some thought, but from the introduction text I can see a potential use case in two of my projects. Unfortunately, I will not be able to join (late notice) with my projects and COP27 asking all my time in this period; are you recording, and sharing the recordings, also, I would be interested in the slides (if there are any)?

Especially the section on evidence based policy creation will be relevant to an UNDP project for climate change risk adaptation; my central question would be around how to establish a network when there is limited information about the social demographics in a region, and if it is possible to substitute data with information from surrounding regions, but what would this substitution (if possible) do with the prediction power of the network and thus how strong is the evidence.

These are just some thoughts, and perhaps my thinking is completely of the mark, so having access to the material would at least bring my understanding at level, before commenting more.

Enjoy the meeting, and if the events are back in person I will visit.

Kind regards,

Gijs

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