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SUMMARY:3rd NETWORKS Match Makers Seminar
DESCRIPTION:Lecture by Frank Takes \n\n\n\nThe Networks Match Makers seminar series started in October 2020 after a succesfull workshop in January 2020\, called NETWORKS Matchmaking Event. In this series we bring together network scientists from the social and economic sciences with network scientists from mathematics and computer science\, with the goal to explore the opportunity to build synergies. \n\n\n\nThe third seminar takes place in the afternoon of October 1\, 2021\, and will be held online. \n\n\n\nFrank Takes is assistant professor at the computer science department (LIACS) of Leiden University. Frank will talk about ‘Population-scale social network analysis’. \n\n\n\nPopulation-scale social network analysis \n\n\n\nThis talk considers responsibly anonymized population-scale social network data on all 17 million inhabitants of the Netherlands. The data is sourced from country-wide administrative register data\, enabling the discovery of population-scale insights into a society. I will show how the analysis of a population-scale multilayer network of family\, work\, school\, household and neighborhood relations enables us to revisit the well-known small-world phenomenon from a unique angle. Moreover\, I discuss how the type of 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.
URL:https://www.popnet.io/events/3rd-networks-match-makers-seminar/
CATEGORIES:Conference talk
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DTSTART;TZID=Europe/Amsterdam:20211011T100000
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SUMMARY:POPNET Connects with Milena Tsvetkova
DESCRIPTION:Please register for the seminar via the button. You will receive a link to the virtual meeting via email.  \n\n\n\n\nRegister\n\n\n\n\nUsing networks to study inequality: two examples \n\n\n\nDo daily decisions and social interactions reproduce socioeconomic inequality? Limited resources could drive self-defeating behaviour\, strain interactions with others\, and restrict access to valuable information in ways that reinforce people’s disadvantaged position\, while already abundant resources could beget additional advantages in ways that make the rich richer. I will present two projects that use radically different computational and analytical methods to address this general hypothesis. In the first example\, we conduct online network cooperation experiments to study whether the visibility of outcome-relevant resources (ability\, intelligence\, knowledge\, etc.) and the visibility of wealth could improve inequality. In the second example\, we analyse the bipartite network of verified Twitter accounts of companies\, brands\, and organizations and their followers to estimate the socioeconomic status of individual Twitter users.  \n\n\n\nAbout Milena Tsvetkova \n\n\n\n\n\n\n\nMilena Tsvetkova is Assistant Professor of Computational Social Science at the Department of Methodology at the London School of Economics and Political Science. She completed her PhD in Sociology at Cornell University and postdoctoral research at the Oxford Internet Institute. Her research interests lie in the fields of computational social science. She uses large-scale web-based social interaction experiments\, network analysis of online data\, and agent-based modelling to investigate fundamental social phenomena such as cooperation\, social contagion\, segregation\, and inequality.
URL:https://www.popnet.io/events/popnet-connects-with-milena-tsvetkova/
CATEGORIES:Seminar
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