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BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20220913T151600
DTEND;TZID=Europe/Amsterdam:20220913T153600
DTSTAMP:20260611T163733
CREATED:20220909T144902Z
LAST-MODIFIED:20220912T075646Z
UID:932-1663082160-1663083360@www.popnet.io
SUMMARY:The Small-World structure of a population-scale social network
DESCRIPTION:Lecture by Frank Takes\, Eszter Bokànyi\, and Eelke Heemskerk at the 6th European Conference on Social Networks (EUSN 2022).  \n\n\n\nThe analysis of social networks at the level of an entire population provides a unique opportunity to revisit what is perhaps the most fundamental universal finding in the field: the small world phenomenon. Popularized as “six degrees of separation”\, it refers to the remarkably low average node-to-node distances and typically high amount of clustering observed in real-world social networks. \n\n\n\nIn this talk we revisit this concept from the perspective of the multilayer population-scale social network of the Netherlands consisting of over 17 million people and five characteristic layers of connectivity based on family\, household\, school work and neighborhood relations. By means of a comparison with artificially simulated networks originating from the well-known Watts-Strogatz and Newman-Watts-Strogatz models\, we show that each type of connectivity (i.e. each layer) in the considered population-scale social network has a different characteristic function in realizing the small-world structure of the network. In particular\, we show how highly clustered family relations form the backbone of the network\, akin to the initial regular (ring-shaped) graph in the WS model. Then\, work and school relations primarily act as “random” bridges between different parts of the clustered (yet\, on its own not-so-small-world) family network. Such edges are ultimately crucial for realizing the actual small-world connectivity patterns in the complete population-scale social network.  \n\n\n\nApart from the explicit multilayer aspect of our population-scale social network data\, we can also take advantage of node attributes (i.e.\, people’s demographic characteristics) in understanding how the low average distances of the network are realized. We find distinct patterns of assortativity between node pairs that are unconnected in one layer (e.g.\, family) and connected in the other (e.g.\, work). Subsequently\, these patterns are used to improve the rewiring step of the Watts-Strogatz model in an attempt to more accurately represent our population-social network data. Specifically\, this step takes into account empirical patterns of homophily\, utilizing the extent to which connections are more frequently formed between nodes with close spatial and similar demographic attributes\, such as level of education. \n\n\n\nOn the theoretical side\, the talk provides insights into the relevance of the WS model\, more than 20 years after its inception. Moreover\, it highlights the importance of multilayer approaches in explaining the connectivity of multilayer networked systems in the real world\, as well as the relation between similarity of node attributes and links spanning larger distances. Substantively and empirically\, the talk contributes to an understanding of how distances are bridged in a social network. The work has important implications in processes that may take place on networks\, such as diffusion of information\, dissemination of resources\, or epidemic spreading.
URL:https://www.popnet.io/events/the-small-world-structure-of-a-population-scale-social-network/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221021T114500
DTEND;TZID=Europe/Amsterdam:20221021T120000
DTSTAMP:20260611T163733
CREATED:20221014T153015Z
LAST-MODIFIED:20221110T100100Z
UID:954-1666352700-1666353600@www.popnet.io
SUMMARY:Excess closure in a multilayer population-scale social network
DESCRIPTION:Lecture by Eszter Bokànyi at the Conference on Complex Systems \n\n\n\nRecent studies on large-scale social networks successfully utilise the growing abundance of digital data sources such as online social networks or mobile communication datasets to uncover fundamental insights on human interaction [1\, 2\, 3].  \n\n\n\nHowever\, in most of these social network data sources\, the sample of people that are represented by the nodes is biased\, and lack of demographic data makes it hard to assess representativity. Moreover\, it is often not clear what exact social relations these online or communication ties represent\, thus\, it is difficult to interpret findings when the goal is to derive meaningful conclusions about people’s social ties [4].  \n\n\n\nWe overcome a number of these drawbacks by presenting a thorough analysis of the complete structure of a 17M node population-scale social network of the Netherlands containing roughly 1.6B edges. This network is derived from highly curated official data sources of the country’s national statistics institute and includes every registered resident in 2018. The edges cover several social relationships: family\, household\, work\, school\, and neighbor. We model each of these edge types as a layer of a node-aligned multilayer network.  \n\n\n\nIn addition\, we have rich individual-level demographic and socio-economic attributes on the nodes (people) available. We consider the network to be a representation of the social opportunity structure in the Netherlands.  \n\n\n\nHere\, we present the first results that show how this population-scale social network is markedly different from many of the large-scale social networks we typically study and reflect on the consequences for computational social science. Below\, we in particular do so by revisiting the well-known concept of closure.  \n\n\n\nClosure is important because individuals have very different resource structures encoded into their social relationships throughout their lives or across demographic groups\, which affects their access to opportunities and information [5]. However\, if we choose to measure closure in a complete population scale social network through traditional local clustering coefficient on the separate layers\, we would get values close to 1. By unioning edges from all layers\, despite the average local clustering coefficient low- ering to 0.40\, it is still unable to resolve potential overlaps or bridges between edges from different layers in people’s egonetworks.  \n\n\n\nTo overcome this problem\, we propose a normalized clustering coefficient that we call excess closure\, that fully exploits the multilayer structure of the networks\, and captures the fraction of triangles in people’s social circles that span across multiple types of relationships.  \n\n\n\nFigure 1 shows how degree and excess closure change with age (a demographic attribute) in the population. Young children have low degrees and very high excess closure since they are only part of family\, neighborhood\, and household structures. Subsequent levels of education paired with working opportunities come with both an increasing median degree\, and decreasing excess closure\, reaching its minimum Fig. 1. Median degree (red) and median excess closure (blue) in ego networks of people of a certain age. Shaded areas are the 25th and 75th percentiles for each age year. around the university age. Working years are characterized by a slight increase in closure\, and gradually decreasing degree\, giving place to low degrees and increased closure in retirement years.  \n\n\n\nOur new normalized multilayer clustering coefficient measure excess closure helps to analyse complete large-scale social networks. The measure captures overlap and bridging between edges of different types in the egonetwork of an individual. We find that excess closure varies across demographic groups as well as throughout people’s lives and it gives a more finegrained understanding of closure in multi-layer population-scale social network data. Our results show a sharp transition from closed to open network structures as young adults engage in higher levels of education\, and a reverse process as people retire. These measurements are first steps in building both methods and universal insights on the rich network structure of highly curated population-level network datasets.  \n\n\n\nFig. 1. Median degree (red) and median excess closure (blue) in ego networks of people of a certain age. Shaded areas are the 25th and 75th percentiles for each age year.\n\n\n\nReferences [1] N. Eagle\, A. S. Pentland\, and D. Lazer. “Inferring Friendship Network Structure by Using Mobile Phone Data.” In: Proceedings of the National Academy of Sciences of the United States of America 106.36 (2009)\, pp. 15274–15278. [2] P. S. Park\, J. E. Blumenstock\, and M. W. Macy. “The Strength of Long-Range Ties in Population-Scale Social Networks”. In: Science 362.6421 (2018)\, pp. 1410–1413. [3] M. Bailey et al. “Social Connectedness: Measurement\, Determinants\, and Effects”. In: Journal of Economic Perspectives 32.3 (2018)\, pp. 259–280. [4] D. Lazer et al. “Meaningful Measures of Human Society in the Twenty-First Century”. In: Nature 595.7866 (2021)\, pp. 189–196. [5] G. T  ́oth et al. “Inequality Is Rising Where Social Network Segregation Interacts with Urban Topology”. In: Nature Communications 12.1 (2021)\, p. 1143
URL:https://www.popnet.io/events/excess-closure-in-a-multilayer-population-scale-social-network/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221103T161500
DTEND;TZID=Europe/Amsterdam:20221103T171500
DTSTAMP:20260611T163733
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20221116T070000
DTEND;TZID=Europe/Amsterdam:20221116T160000
DTSTAMP:20260611T163733
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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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230629T184000
DTEND;TZID=Europe/Amsterdam:20230629T200000
DTSTAMP:20260611T163733
CREATED:20230512T123227Z
LAST-MODIFIED:20230512T123303Z
UID:1091-1688064000-1688068800@www.popnet.io
SUMMARY:The anatomy of a population-scale social network
DESCRIPTION:On Thursday 29 June\, POPNET Postdoctoral Researcher Eszter Bokányi will present her work on “The anatomy of a population-scale social network” at Sunbelt 2023\, which will take place in Portland\, Oregon.
URL:https://www.popnet.io/events/the-anatomy-of-a-population-scale-social-network-5/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230629T184000
DTEND;TZID=Europe/Amsterdam:20230629T200000
DTSTAMP:20260611T163733
CREATED:20230512T123924Z
LAST-MODIFIED:20230512T123925Z
UID:1097-1688064000-1688068800@www.popnet.io
SUMMARY:Social-economic segregation in a Population-Scale Social Network
DESCRIPTION:On Thursday 29 June\, POPNET PhD candidate Yuliia Kazmina will present her work on “Social-economic segregation in a Population-Scale Social Network” at Sunbelt 2023\, which will take place in Portland\, Oregon.
URL:https://www.popnet.io/events/social-economic-segregation-in-a-population-scale-social-network/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230629T184000
DTEND;TZID=Europe/Amsterdam:20230629T200000
DTSTAMP:20260611T163733
CREATED:20230512T123924Z
LAST-MODIFIED:20230512T124244Z
UID:1099-1688064000-1688068800@www.popnet.io
SUMMARY:The small-world structure of a population-scale social network
DESCRIPTION:On Thursday 29 June\, POPNET PI Frank Takes will present his work on “The small-world structure of a population-scale social network” at Sunbelt 2023\, which will take place in Portland\, Oregon.
URL:https://www.popnet.io/events/the-small-world-structure-of-a-population-scale-social-network-2/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20230629T213000
DTEND;TZID=Europe/Amsterdam:20230629T225000
DTSTAMP:20260611T163733
CREATED:20230512T123603Z
LAST-MODIFIED:20230512T123707Z
UID:1095-1688074200-1688079000@www.popnet.io
SUMMARY:Node anonymity in networks: The infectiousness of uniqueness
DESCRIPTION:On Thursday 29 June\, POPNET PhD candidate Rachel de Jong will present her work on “Node anonymity in networks: The infectiousness of uniqueness” at Sunbelt 2023\, which will take place in Portland\, Oregon.
URL:https://www.popnet.io/events/node-anonymity-in-networks-the-infectiousness-of-uniqueness/
CATEGORIES:Conference talk
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END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20240626T000000
DTEND;TZID=Europe/Amsterdam:20240629T235959
DTSTAMP:20260611T163733
CREATED:20240624T113513Z
LAST-MODIFIED:20240624T113516Z
UID:1257-1719360000-1719705599@www.popnet.io
SUMMARY:POPNET presents their work during Sunbelt Conference 2024
DESCRIPTION:POPNET proudly joins the 44th edition of the Sunbelt Conference in Edinburgh from 24th June to June 30th 2024. The Sunbelt Conference is part of the International Network for Social Network Analysis (INSNA)\, providing an interdisciplinary venue for social scientists\, mathematicians\, computer scientists\, ethnologists\, and others to present current work in the area of social networks. \n\n\n\nExploring Social Network Analysis  \n\n\n\nIn alignment with POPNET’s aim to unlock longitudinal social network data on the Dutch population\, this year theme of the Sunbelt 2024 is ‘Networks and Resilience’. Throughout the conference\, various members of POPNET will give talks in the field of social network analysis. Social capital\, network clustering\, and family networks are just a few examples of the topics that will be covered at Sunbelt 2024. \n\n\n\nFind below a list of the titles they will present during the conference: \n\n\n\n\n26 June\, 14:30: “Is Social Capital Good for you?”\, by Heemskerk\, Eelke; Takes\, Frank W. .\n\n\n\n26 June\, 14:30: “Social Network Determinants of Economic Prosperity in a Longitudinal Population-scale Social Network”\, by Kazmina\, Yuliia; Heemskerk\, Eelke; Bokanyi\, Eszter; Takes\, Frank W. .\n\n\n\n27 June\, 8:30: “Parenthood status of siblings\, half-siblings and cousins and entry into parenthood. A horizontal kinship network approach”\, by de Bel\, Vera; Artamonova\, Alyona; Hiraoka\, Takayuki; Danielsbacka\, Mirkka; Tanskanen\, Antti; van Duijn\, Marijtje.\n\n\n\n27 June\, 10:40: “Large and small-scale dynamics of a longitudinal population-scale social network”\, by Bokanyi\, Eszter; Kazmina\, Yuliia; van der Kooij\, Emilia; Takes\, Frank; Heemskerk\, Eelke.\n\n\n\n29 June\, 14:00: “Connectivity and community structure of online and register-based population-scale social networks”\, by Menyhért\, Márton; Bokányi\, Eszter; Corten\, Rens; Heemskerk\, Eelke; Kazmina\, Yuliia; Takes\, Frank W. .
URL:https://www.popnet.io/events/popnet-presents-their-work-during-sunbelt-conference-2024/
CATEGORIES:Conference talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20240627T083000
DTEND;TZID=Europe/Amsterdam:20240627T101000
DTSTAMP:20260611T163733
CREATED:20240603T113716Z
LAST-MODIFIED:20240603T113832Z
UID:1249-1719477000-1719483000@www.popnet.io
SUMMARY:Parenthood status of siblings\, half-siblings and cousins and entry into parenthood. A horizontal kinship network approach
DESCRIPTION:On June 27\, Vera de Bel\, Alyona Artamonova\, Takayuki Hiraoka\, Mirkka Danielsbacka\, Antti Tanskanen\, Marijtje van Duijn will present their work on “Parenthood status of siblings\, half-siblings and cousins and entry into parenthood. A horizontal kinship network approach” at Sunbelt 2024\, which will take place in at Heriot-Watt University\, Edinburgh. \n\n\n\nAbstract\n\n\n\nHorizontal kinship ties last a lifetime\, and life-course transitions of horizontal kin are known to be interconnected. Prior research\, with a focus on siblings\, has demonstrated their influence on various life events\, including home leaving (Her\, Vergauwen\, & Mortelmans\, 2022)\, marriage and divorce behavior (Buyukkececi & Leopold\, 2021)\, and fertility (Buyukkececi & Leopold\, 2021; Lyngstad & Prskawetz\, 2010). However\, siblings are just one example of individuals’ horizontal kin\, and the impact extends to half-siblings and cousins\, shaping both individual trajectories and those of their relatives. Moreover\, the influence of horizontal kin may vary based on factors such as the degree of relatedness (full siblings\, half-siblings\, or cousins)\, kin’s gender ((half-)brothers\, (half-)sisters\, male or female cousins)\, and lineage (paternal or maternal side of the family). This study seeks to analyze the complete horizontal kinship network to understand how individuals’ entry into parenthood is associated with the parenthood status of their horizontal kin. More specifically\, the study examines whether 1) close kin compared to more distant kin\, 2) female compared to male kin\, and 3) maternal compared to paternal kin have a stronger influence on an individual’s entry into parenthood. Utilizing unique registry data that documents the kinship networks of the entire Dutch (van der Laan\, de Jonge\, Das\, Te Riele\, & Emery\, 2022) and Finnish population\, the study will employ a multi-level model considering the nested structure and dependence of relationships (Snijders & Bosker\, 2012; van Duijn\, 2013). First results and a comparison between the Dutch and Finnish contexts will be presented.
URL:https://www.popnet.io/events/parenthood-status-of-siblings-half-siblings-and-cousins-and-entry-into-parenthood-a-horizontal-kinship-network-approach/
CATEGORIES:Conference talk
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20241018T100000
DTEND;TZID=Europe/Amsterdam:20241018T190000
DTSTAMP:20260611T163733
CREATED:20241001T125809Z
LAST-MODIFIED:20241009T095143Z
UID:1278-1729245600-1729278000@www.popnet.io
SUMMARY:Increasing mobility is linked to decreasing cohesion of personal networks overthe lifecourse of an entire population
DESCRIPTION:On October 18\, Eszter Bokányi will present her work on “Increasing mobility is linked to decreasing cohesion of personal networks over the lifecourse of an entire population” at the Dutch NetSci Symposium\, which will take place at Eindhoven University of Technology. \n\n\n\n \n\n\n\nAbstract\n\n\n\nGrowing accessibility between places and a changing society foster higher human mobility both daily and long-term\, which results in an increased social connectivity between faraway places. Thus\, geographic displacement creates new connections and at the same time rearranges the existing spatial structure of social networks. Both of these mechanisms are little understood in the existing literature of social network formation processes. Moreover\, up until now\, it has also been a challenge to systematically follow the temporal evolution of an entire population’s social network structure. \n\n\n\nIn this work\, we use a unique longitudinal population-scale network dataset sourced from Statistics Netherlands. This network contains family\, work\, school\, household\, and next-door neighbor connections derived from administrative registers\, that together constitute a multilayer social opportunity structure for all residents of the Netherlands between 2009 and 2022. We follow the patterns of individuals’ network surroundings over time\, and measure size\, closure\, and geographical dispersion of ego networks. Size is captured by degree\, closure by excess closure [1]\, which is based on the node clustering coefficient. Geographical dispersion is given by the average distance from network neighbors\, and the average share of network neighbors in the same municipality or the same next-door neighborhood as the ego. \n\n\n\nThe three findings presented in this work are that while the average size of ego networks stays stable over the observed period\, average closure drops by as much as 10%\, and the average distance from network neighbors grows\, while the average share of network neighbors in the same geographic area decreases. We use multivariate regressions to show that the observed decrease in the closure is significantly linked to the growing geographic dispersion\, thus\, the increasing daily and long-term mobility of people. We control for demographic and socio-economic background including the age\, migrant generation\, income\, and whether people attend school and have employment. The regressions confirm that beyond degree and demographics\, variables that capture people’s mobility are linked to the opening up of individual networks. \n\n\n\nThis work is the first of its kind that aims to map the temporal network of an entire population structure comprehensively. As such\, it offers a starting point for a wide variety of impactful network science research at the level of a complete population. \n\n\n\n\n\n\n\n[1] Bokányi\, E.\, Heemskerk\, E. M.\, & Takes\, F. W. (2023). The anatomy of a population-scale social network. Scientific Reports\, 13(1)\, 9209.
URL:https://www.popnet.io/events/increasing-mobility-is-linked-to-decreasing-cohesion-of-personal-networks-overthe-lifecourse-of-an-entire-population/
CATEGORIES:Conference talk
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END:VEVENT
END:VCALENDAR