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X-WR-CALDESC:Events for POPNET
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DTSTART;TZID=Europe/Amsterdam:20221103T160000
DTEND;TZID=Europe/Amsterdam:20221103T170000
DTSTAMP:20260503T202433
CREATED:20221103T122720Z
LAST-MODIFIED:20221103T122722Z
UID:990-1667491200-1667494800@www.popnet.io
SUMMARY:The anatomy of a population-scale social network
DESCRIPTION:Lecture by Eszter Bokányi for the Network Seminar series of the Learning Planet Institute \n\n\n\n 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.
URL:https://www.popnet.io/events/the-anatomy-of-a-population-scale-social-network-4/
CATEGORIES:Lecture
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BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221103T161500
DTEND;TZID=Europe/Amsterdam:20221103T171500
DTSTAMP:20260503T202433
CREATED:20221003T120109Z
LAST-MODIFIED:20221014T153328Z
UID:937-1667492100-1667495700@www.popnet.io
SUMMARY:Capturing the social fabric: Population-scale socio-economic segregation patterns
DESCRIPTION:Conference talk by Yuliia Kazmina at the Odissei Conference for Social Science in the Netherlands 2022 in session 4.1.  \n\n\n\nSegregation is a widely studied issue traditionally explored from the point of the spatial distribution of different groups as defined by any individual attribute such as race\, religion\, social class\, etc. Nevertheless\, we argue that the issues of persistent segregation\, specifically socio-economic segregation\, are networked phenomena and should be studied as such. In this paper\, we make a methodological contribution that would allow the scholarship and policymakers to move away from a traditional spatial understanding of segregation that ignores interactions beyond neighborhoods and shift the focus of segregation measurement to the social network aspect applied to a diverse set of previously unexplored distinct social contexts. \n\n\n\nThe study is based on the Dutch population register data sourced from multiple existing sub-registers that contain information on formal ties and affiliations of ~17 million legal residents in multiple social contexts such as kinship\, household\, neighborhood\, school\, and work. With the multiplex network of geospatially embedded formal ties in hand\, we aim to observe to what extent areas of social segregation are clustered in geospatially embedded social networks\, and how each network layer contributes to the issue. More specifically\, we measure to what extent Dutch residents in different municipalities are exposed to individuals of different socio-economic statuses in diverse social contexts and what social contexts provide diverse social contact opportunities with respect to the socio-economic status and\, on the contrary\, what social contexts play a role of socio-economic bubbles. Our findings suggest great heterogeneity in socio-economic assortativity between different social contexts (the layers of the analysed network) as well as different municipalities.
URL:https://www.popnet.io/events/capturing-the-social-fabric-population-scale-socio-economic-segregation-patterns-3/
CATEGORIES:Conference talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221116T070000
DTEND;TZID=Europe/Amsterdam:20221116T160000
DTSTAMP:20260503T202433
CREATED:20221003T120610Z
LAST-MODIFIED:20221003T142621Z
UID:940-1668582000-1668614400@www.popnet.io
SUMMARY:Network-based study of segregation and social capital in the Netherlands using population-scale social network data derived from official population registers
DESCRIPTION:Conference talk by Yuliia Kazmina at the Dutch Demography Day 2022.  \n\n\n\nUsing population-scale social network data derived from official population registers\, we propose a network-based study of segregation and social capital in the Netherlands.  \n\n\n\nSegregation is a widely studied issue traditionally explored from the point of the spatial distribution of different groups as defined by any individual attribute such as race\, religion\, social class\, etc. Nevertheless\, we argue that the issues of persistent segregation\, specifically socio-economic segregation\, are networked phenomena and should be studied as such. We measure to what extent Dutch residents in different municipalities are exposed to individuals of different socio-economic statuses in diverse social contexts and what social contexts provide diverse social contact opportunities with respect to the socio-economic status and\, on the contrary\, what social contexts play a role of socio-economic bubbles. Our findings suggest great heterogeneity in socio-economic assortativity between different social contexts as well as different municipalities.  \n\n\n\nSocial capital can be seen as the value and resources found in social structures which enable collective action. It is most often measured indirectly based on theoretical argumentation using data on its expected outcomes\, such as civic participation or volunteering rates. We determine the relationship between network measures of bridging and bonding social capital and volunteering rates. The results of the regression analyses show a significant relation between rates of social bonding and social capital. Network measures related to social bridging have a significant but weaker and negative impact on social capital. This suggests that the type of social capital must be carefully considered when attempting to measure social capital using networks. Our work presents the first major steps for the measurement of social capital using population-scale network data. The findings can be valuable to anyone measuring social capital in networks\, paving the way for informed decision-making aimed at increasing social capital of\, for example\, minority groups.
URL:https://www.popnet.io/events/network-based-study-of-segregation-and-social-capital-in-the-netherlands-using-population-scale-social-network-data-derived-from-official-population-registers/
CATEGORIES:Conference talk
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BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221121T120000
DTEND;TZID=Europe/Amsterdam:20221121T130000
DTSTAMP:20260503T202433
CREATED:20221103T113344Z
LAST-MODIFIED:20221103T114807Z
UID:977-1669032000-1669035600@www.popnet.io
SUMMARY:POPNET Connects with Ágnes Backhausz
DESCRIPTION:Please register for the seminar via the button. You will receive a confirmation via email.  \n\n\n\n\nRegister to attend online\n\n\n\n\n \n\n\n\nThe impact of spatial and social structure on an SIR epidemic on a weighted multilayer network\n\n\n\nThe household model defined and analyzed by Frank Ball consists of households (small cliques of the same size)\, connected to each other with edges of smaller weight. However\, this model does not include dense clusters other than the households themselves\, hence\, for example\, school classes are not represented. Starting from this\, in the current work we were interested in the behaviour of an SIR process on a more complex random graph model\, based on the layer of households\, a layer of schools and workplaces\, the layer representing the spatial structure and a fourth layer representing communal places. We studied the sensitivity of the model for the different parameters\, looked for estimates of the parameters in a simpler case\, and compared different vaccination strategies. Our model and the main results will be presented in the talk. \n\n\n\nJoint work with István Z. Kiss\, Péter L. Simon and György Székely. \n\n\n\n\n\n\n\nAbout Ágnes Backhausz\n\n\n\nÁgnes Backhausz obtained her PhD in 2013 at ELTE Eötvös Loránd University\, Budapest\, Hungary\, with a thesis on preferential attachment random graphs. As a postdoctoral researcher\, she spent two years at Alfred Renyi Institute of Mathematics\, working in the “Limits of Structures” research group. Her research topic includes random graphs\, graph limit theory\, and more recently epidemic spread on random networks. Currently she is an assistant professor at ELTE Eötvös Loránd University\, Budapest\, Hungary\, and also a research fellow at Alfréd Rényi Institute of Mathematics.
URL:https://www.popnet.io/events/popnet-connects-with-agnes-backhausz/
CATEGORIES:Seminar
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