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X-WR-CALDESC:Events for POPNET
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BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20240628T172000
DTEND;TZID=Europe/Amsterdam:20240628T190000
DTSTAMP:20260526T145557
CREATED:20240205T115516Z
LAST-MODIFIED:20240603T093933Z
UID:1221-1719595200-1719601200@www.popnet.io
SUMMARY:Contacts in contexts: A population-scale social network approach to the study of close intergroup social ties
DESCRIPTION:On June 28\, Nicolás Soler\, PhD Candidate (Erasmus University Rotterdam) and POPNET Fellow\, will give a lecture about a new approach that investigates social context in intergroup social ties across multiple contexts. \n\n\n\nAbstract\n\n\n\nClose intergroup social ties provide fertile ground to cultivate mutual trust and tolerance. Social context shapes the opportunities to form such ties\, but what is exactly the relationship between opportunities and realised intergroup social ties? When assessing the importance of social context\, previous quantitative research has faced a trade-off between generalisability and granularity in data collection. The challenge is to study the relevance of social context in intergroup social ties across multiple contexts\, in detail\, and at a large scale. To do so\, we map social context using newly available population-scale social network data from the Netherlands. We link them to survey data on close intergroup social ties. We showcase our novel approach by investigating which contexts sustain close social ties between immigrants and natives\, i.e. individuals born and residing in the Netherlands. Our results confirm that natives who have more opportunities to interact with immigrants are more likely to have a close intergroup social tie with them. We find that this effect is stronger when the opportunities for intergroup interaction arise in private rather than public contexts. We also find that natives with at least one immigrant parent are important brokers in this type of intergroup social ties. \n\n\n\nCo-authored with Eelke and Yuliia. Presented as poster presentation.
URL:https://www.popnet.io/events/promise-and-perils-of-population-scale-social-network-analysis-2/
CATEGORIES:Lecture
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20231026T153000
DTEND;TZID=Europe/Amsterdam:20231026T170000
DTSTAMP:20260526T145557
CREATED:20240205T113331Z
LAST-MODIFIED:20240205T114422Z
UID:1219-1698334200-1698339600@www.popnet.io
SUMMARY:Promise and perils of population-scale social network analysis
DESCRIPTION:On Thursday 26 October\, POPNET PI Frank Takes will present his work online for the IAS lecture series of the Institute for Analytical Sociology in Norrköping\, Sweden. \n\n\n\nAbstract\n\n\n\nA relatively recently emerged line of research is dedicated to harnessing large-scale population register data to address enduring questions within the realm of social science. In this presentation\, we will specifically delve into the network dimension of such data\, with a focus on data from the POPNET project\, covering over 17 million people (i.e.\, the entirety of the Netherlands) and their ca. 800M family\, household \, school\, work and next-door neighbor connections. We highlight the potential inherently present in this type of curated and comprehensive social network data through illustrative examples of results related to topics such as social capital\, segregation\, and migration. Furthermore\, we will explore several methodological considerations and challenges related to under- and oversampling of individual connections through opportunity structures\, including findings on the veracity of skewed degree distributions in the real world. We also highlight network-structure related concerns w.r.t. privacy\, in particular disclosure risk and more in general the anonymization of network data for scientific research.
URL:https://www.popnet.io/events/promise-and-perils/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/04/linkoping-university-vector-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230516T100000
DTEND;TZID=Europe/Amsterdam:20230516T110000
DTSTAMP:20260526T145557
CREATED:20230328T133438Z
LAST-MODIFIED:20230330T075655Z
UID:1063-1684231200-1684234800@www.popnet.io
SUMMARY:Segregation in population scale social networks
DESCRIPTION:Lecture by Eelke Heemskerk and Yuliia Kazmina at the Sociology Department of Utrecht University \n\n\n\nWe propose a social network-aware approach to study socio-economic segregation. The key question is whether patterns of segregation are more pronounced in social networks than the common spatial manifestations of segregation. We conduct a population-scale social network analysis to uncover socio-economic segregation at a comprehensive and highly granular level. At the basis of this analysis is high quality register data consisting of complete information on $\sim$17.2 million registered residents of the Netherlands that are connected through 1.3 billion ties distributed over four distinct tie types. By comparing income assortativity between the social network and the spatial perspective\, we find that the social network structure exhibits  a factor of two higher segregation.  This may signal  that while at a particular  scale of spatial aggregation (e.g.\, the geographical  neighborhood)\, patterns of socio-economic segregation appear to be minimal\,  they in fact persist in the underlying social network structure. Furthermore\, we discover higher socioeconomic segregation in larger cities as opposed to a widespread view of cities as hubs for diverse socioeconomic mixing. A population scale  social network perspective hence offers a way to uncover hitherto “hidden” segregation that extends beyond spatial neighborhoods and infiltrates multiple aspects of human life.
URL:https://www.popnet.io/events/segregation-in-population-scale-social-networks/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/jpeg:https://www.popnet.io/wp-content/uploads/2023/03/Smaller-logo-page-Ultecht-University.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221103T160000
DTEND;TZID=Europe/Amsterdam:20221103T170000
DTSTAMP:20260526T145557
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
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/11/LPI-large-no-tagline-twitter.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220616T130000
DTEND;TZID=Europe/Amsterdam:20220616T140000
DTSTAMP:20260526T145557
CREATED:20220523T072954Z
LAST-MODIFIED:20220617T114704Z
UID:858-1655384400-1655388000@www.popnet.io
SUMMARY:Population-scale Social Network Analysis
DESCRIPTION:Lecture by Frank Takes for the Interaction Data Lab of the Center for Research and Interdisciplinarity (CRI) in Paris. \n\n\n\n\n\nAbstract\n\n\n\nThis talk considers responsibly anonymized population-scale social network data on all 17 million inhabitants of the Netherlands. The data stems from country-wide administrative register data\, and has the potential to shed new light on contemporary social scientific problems such as segregation\, inequality\, loneliness and poverty. The talk discusses how the formal links (family\, household\, work\, school and neighbor ties) in this social network require one to critically rethink network science concepts such as the unit of analysis\, measurement errors effects and the boundary specification problem. Moreover\, it allows us to in a unique way revisit the well-known concept of closure and the small-world phenomenon in a population-scale social network context. The talk furthermore presents initial findings on the relation between the network structure and spatial distribution of the population.
URL:https://www.popnet.io/events/population-scale-social-network-analysis-5/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/05/screen-shot-2020-11-13-at-1.24.22-pm.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220512T133000
DTEND;TZID=Europe/Amsterdam:20220512T150000
DTSTAMP:20260526T145557
CREATED:20220426T090638Z
LAST-MODIFIED:20220426T090640Z
UID:831-1652362200-1652367600@www.popnet.io
SUMMARY:The anatomy of a population-scale social network
DESCRIPTION:Lecture for the Institute for Analytical Sociology of Linköping University\, by Eszter Bokányi. \n\n\n\nAbstract: The analysis of large-scale societal networks has recently seen tremendous growth\, in part because of the relative abundance of digital data sources such as online social networks or mobile communication datasets. However\, most of these data sources lack demographic data on users or are uncertain with respect to the representativity of the user sample. Moreover\, it is often not clear what exact social relations these online or communication ties represent\, thus\, it is difficult to interpret findings. This talk will attempt to overcome a number of these drawbacks by presenting a thorough overview of the structure of a 17M node multilayer population-scale social network of the Netherlands containing roughly 1.6B edges derived from highly curated official data sources of CBS Netherlands. First\, we show how the degree distribution of this network is a composition of the degree distributions of the different types of edges. In the overall degree distribution\, we find a characteristic value that is in sharp contrast to the scale-free or other fat-tailed distributions found in online social networks or communication networks. Second\, we discuss different types of clustering in this multilayer network\, and show how closed or open network structures emerge for people of certain ages. In particular\, we introduce a normalized multilayer clustering coefficient that we call excess closure\, that captures the fraction of triangles in people’s social circles that span across multiple types of relationships. Finally\, we show that long-range ties that span large distances are very scarce in this network\, which is in contrast to findings in online social networks\, and does not promote fast and efficient diffusion processes over this structure\, despite average path lengths being low. Our measurements are first steps in building both methods and universal insights on the rich network structure of highly curated population-level network datasets.
URL:https://www.popnet.io/events/the-anatomy-of-a-population-scale-social-network/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/04/linkoping-university-vector-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220429T160000
DTEND;TZID=Europe/Amsterdam:20220429T170000
DTSTAMP:20260526T145557
CREATED:20220419T093023Z
LAST-MODIFIED:20220421T121550Z
UID:798-1651248000-1651251600@www.popnet.io
SUMMARY:Population-scale Social Network Analysis
DESCRIPTION:Lecture by co-director Frank Takes for the Maths and Statistics Department in the University of Limerick. \n\n\n\nAbstract\n\n\n\nThis talk considers responsibly anonymized population-scale social network data on all 17 million inhabitants of the Netherlands. The data stems from country-wide administrative register data\, and has the potential to shed new light on contemporary social scientific problems such as segregation\, inequality\, loneliness and poverty. The talk discusses how the formal links (family\, household\, work\, school and neighbor ties) in this social network require one to critically rethink network science concepts such as the unit of analysis\, measurement errors effects and the boundary specification problem. Moreover\, it allows us to in a unique way revisit the well-known concept of closure and the small-world phenomenon in a population-scale social network context. The talk furthermore presents initial findings on the relation between the network structure and spatial distribution of the population.
URL:https://www.popnet.io/events/population-scale-social-network-analysis-4/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/jpeg:https://www.popnet.io/wp-content/uploads/2022/04/UL-logo.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220422T150000
DTEND;TZID=Europe/Amsterdam:20220422T160000
DTSTAMP:20260526T145557
CREATED:20220419T091322Z
LAST-MODIFIED:20220421T120822Z
UID:795-1650639600-1650643200@www.popnet.io
SUMMARY:LCN2 seminar: The anatomy of a population-scale social network
DESCRIPTION:Lecture for Leiden Complex Networks Network (LCN2) by Eszter Bokányi.Title: The anatomy of a population-scale social network \n\n\n\nAbstract: The analysis of large-scale societal networks has recently seen tremendous growth\, in part because of the relative abundance of digital data sources such as online social networks or mobile communication datasets. However\, most of these data sources lack demographic data on users or are uncertain with respect to the representativity of the user sample. Moreover\, it is often not clear what exact social relations these online or communication ties represent\, thus\, it is difficult to interpret findings. This talk will attempt to overcome a number of these drawbacks by presenting a thorough overview of the structure of a 17M node multilayer population-scale social network of the Netherlands containing roughly 1.6B edges derived from highly curated official data sources of CBS Netherlands. First\, we show how the degree distribution of this network is a composition of the degree distributions of the different types of edges. In the overall degree distribution\, we find a characteristic value that is in sharp contrast to the scale-free or other fat-tailed distributions found in online social networks or communication networks. Second\, we discuss different types of clustering in this multilayer network\, and show how closed or open network structures emerge for people of certain ages. In particular\, we introduce a normalized multilayer clustering coefficient that we call excess closure\, that captures the fraction of triangles in people’s social circles that span across multiple types of relationships. Finally\, we show that long-range ties that span large distances are very scarce in this network\, which is in contrast to findings in online social networks\, and does not promote fast and efficient diffusion processes over this structure\, despite average path lengths being low. Our measurements are first steps in building both methods and universal insights on the rich network structure of highly curated population-level network datasets.
URL:https://www.popnet.io/events/lcn2-seminar-the-anatomy-of-a-population-scale-social-network/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/04/LCN2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220421T151500
DTEND;TZID=Europe/Amsterdam:20220421T161500
DTSTAMP:20260526T145557
CREATED:20220419T090635Z
LAST-MODIFIED:20220421T120716Z
UID:792-1650554100-1650557700@www.popnet.io
SUMMARY:Research Colloquium on Business Informatics
DESCRIPTION:As part of the Research Colloquium on Information Systems and Data Science of the Institute of Information Systems of Leuphana University Lüneburg\, co-director Frank Takes will speak on “Population-scale Social Network Analysis” via Zoom. \n\n\n\nAbstract\n\n\n\nThis talk considers responsibly anonymized population-scale social network data on all 17 million inhabitants of the Netherlands. The data stems from country-wide administrative register data\, and has the potential to shed new light on contemporary social scientific problems such as segregation\, inequality\, loneliness and poverty. The talk discusses how the formal links (family\, household\, work\, school and neighbor ties) in this social network require one to critically rethink network analysis concepts such as the unit of analysis\, measurement errors effects and the boundary specification problem. Moreover\, it allows us to in a unique way revisit the well-known concept of closure and the small-world phenomenon in a population-scale social network context. The talk furthermore presents initial findings on the relation between the network structure and spatial distribution of the population.
URL:https://www.popnet.io/events/research-colloquium-on-business-informatics/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/jpeg:https://www.popnet.io/wp-content/uploads/2022/04/Leuphana.jpg
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220121T150000
DTEND;TZID=Europe/Amsterdam:20220121T160000
DTSTAMP:20260526T145557
CREATED:20220117T111449Z
LAST-MODIFIED:20220117T111509Z
UID:725-1642777200-1642780800@www.popnet.io
SUMMARY:Population-scale Social Network Analysis
DESCRIPTION:Seminar at GRAFO – GRUP DE RECERCA EN ANTROPOLOGIA FONAMENTAL I ORIENTADA (University of Barcelona) by Frank Takes and Yuliia Kazmina \n\n\n\nCountry-wide administrative register data\, as studied within the POPNET Project\, enables the discovery of population-scale insights into contemporary social scientific problems such as segregation\, inequality\, loneliness\, and poverty. This talk considers responsibly anonymized population-scale social network data on all 17 million inhabitants of the Netherlands. We discuss how the formal links in this social network require one to critically rethink network analysis concepts such as the unit of analysis\, measurement errors effects and the boundary specification problem\, but also allows us to in a unique way revisit the well-known small-world phenomenon. The talk furthermore presents initial findings on the relation between the network structure and spatial distribution of the population as well as emerging socio-economic inequality and segregation patters.
URL:https://www.popnet.io/events/population-scale-social-network-analysis-3/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2022/01/Grafo-logo.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210831T140000
DTEND;TZID=Europe/Amsterdam:20210831T150000
DTSTAMP:20260526T145557
CREATED:20210827T084317Z
LAST-MODIFIED:20211029T100311Z
UID:613-1630418400-1630422000@www.popnet.io
SUMMARY:Measuring Structural Anonymity in Complex Networks
DESCRIPTION:Master thesis presentation by Rachel de Jong \n\n\n\nWhen sharing sensitive data\, it should be made sure that entities represented in it are sufficiently anonymous in order to avoid a possible breach of privacy. In the field of statistical disclosure control\, this concept is well studied. However\, thus far the majority of work in this field focuses on microdata and (aggregated) tabular data. In this work\, we discuss a new measure for anonymity in networks: d-k-anonymity. It improves upon existing measures (which are in most cases too weak\, too strict\, or not able to account for triangles) by being parametrized in strictness and taking into account all information in the d-neighbourhood of a vertex. This enables the user to select the right level of anonymity based on how much a possible attacker knows. We present an algorithm that can efficiently measure the anonymity and apply it to three well known-graph models with up to 10\,000 vertices\, as well as a real-world network; the full family network of the Netherlands\, consisting of over 15 million vertices. In our experiments\, we find that for graph models most anonymity is lost when measuring 2-k-anonymity\, and vertices quickly all become unique as the edge density increases. For the family network\, over 2.7 million vertices have an anonymity of 1 when measuring 5-k-anonymity\, implying that they are uniquely identifiable when their exact position in their 5-neighbourhood is known. \n\n\n\nSupervisors: Frank Takes and Mark van der Loo (CBS) \n\n\n\nIf you wish to join this presentation\, please send an email to popnet@uva.nl.
URL:https://www.popnet.io/events/measuring-structural-anonymity-in-complex-networks/
CATEGORIES:Lecture
ATTACH;FMTTYPE=image/jpeg:https://www.popnet.io/wp-content/uploads/2021/05/POPNET-header-scaled.jpg
END:VEVENT
END:VCALENDAR