BEGIN:VCALENDAR
VERSION:2.0
PRODID:-//POPNET - ECPv6.15.20//NONSGML v1.0//EN
CALSCALE:GREGORIAN
METHOD:PUBLISH
X-WR-CALNAME:POPNET
X-ORIGINAL-URL:https://www.popnet.io
X-WR-CALDESC:Events for POPNET
REFRESH-INTERVAL;VALUE=DURATION:PT1H
X-Robots-Tag:noindex
X-PUBLISHED-TTL:PT1H
BEGIN:VTIMEZONE
TZID:Europe/Amsterdam
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20200329T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20201025T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20210328T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20211031T010000
END:STANDARD
BEGIN:DAYLIGHT
TZOFFSETFROM:+0100
TZOFFSETTO:+0200
TZNAME:CEST
DTSTART:20220327T010000
END:DAYLIGHT
BEGIN:STANDARD
TZOFFSETFROM:+0200
TZOFFSETTO:+0100
TZNAME:CET
DTSTART:20221030T010000
END:STANDARD
END:VTIMEZONE
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210728T094500
DTEND;TZID=Europe/Amsterdam:20210728T100000
DTSTAMP:20260503T115933
CREATED:20210719T064140Z
LAST-MODIFIED:20211029T100345Z
UID:558-1627465500-1627466400@www.popnet.io
SUMMARY:The effect of commuting on the income assortativity of social network ties
DESCRIPTION:Conference talk at IC2S2 \n\n\n\nAuthors: Eszter Bokanyi\, Sándor Juhász\, Márton Karsai and Balazs Lengyel \n\n\n\nABSTRACTIn this work\, we investigate home-work locations and mutual followership ties of Twitter users from the top 50 metropolitan areas of the United States. We find that despite the heterogeneity of spatial structures in cities\, above median commuting reduces the income assortativity of social networks by 30% on average.
URL:https://www.popnet.io/events/the-effect-of-commuting-on-the-income-assortativity-of-social-network-ties/
CATEGORIES:Conference talk
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/07/ic2s2.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210709T161500
DTEND;TZID=Europe/Amsterdam:20210709T163000
DTSTAMP:20260503T115933
CREATED:20210707T061007Z
LAST-MODIFIED:20211029T100351Z
UID:529-1625847300-1625848200@www.popnet.io
SUMMARY:The community structure of global scientific collaboration - lecture at Networks2021 conference
DESCRIPTION:Lecture by Frank Takes on the Networks 2021 conference \n\n\n\nAuthors: Hanjo Boekhout; Eelke Heemskerk; Frank Takes \n\n\n\nIn this work we study the structure of global scientific collaboration\, in an attempt to better understand the internationalization of research. In particular\, we are interested in the existence of closely collaborating scientific communities. Indeed\, it is well-known that even though science knows no borders\, collaboration ties are not randomly created between individual scholars. Instead\, we anticipate geographical\, political and cultural factors to play a crucial role in this process. In this paper we set out to empirically investigate to what extent this is the case by providing a large-scale analysis of 23 million publications from Web of Science in the period 2008—2019.
URL:https://www.popnet.io/events/the-community-structure-of-global-scientific-collaboration-lecture-at-networks2021-conference/
CATEGORIES:Conference talk
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/07/vis-hcp10.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210706T204500
DTEND;TZID=Europe/Amsterdam:20210706T210000
DTSTAMP:20260503T115933
CREATED:20210702T072413Z
LAST-MODIFIED:20211029T100401Z
UID:519-1625604300-1625605200@www.popnet.io
SUMMARY:Measuring Anonymity in Complex Networks at Networks 2021 conference
DESCRIPTION:Lecture by Rachel de Jong at Networks2021 conference \n\n\n\nAuthors: Rachel de Jong; Mark van der Loo; Frank Takes \n\n\n\nComplex networks are often used to describe the interactions between individuals or organizations within social or economic systems. In order to comply with regulations regarding privacy and data protection\, such data is frequently anonymized by leaving out personal identifiers of the nodes. However\, in such cases (properties of) a seemingly anonymized individual may still be re-identified based on its structural position in the network [1]. \n\n\n\nThis is particularly relevant for National Statistical Institutes (NSIs) that are applying network science to population scale social network data [2]. When releasing data for research purposes\, NSIs rely on statistical disclosure control (SDC) techniques for data protection [3]. A central concept in this field is anonymity: the number of equivalent data points in an anonymized data set. Anonymity is an essential component in assessing the risk of disclosure. \n\n\n\nThis work presents a method for measuring the disclosure probability of nodes in networks\, that takes as a parameter the amount of information an adversary has about a node’s surrounding structure. We also provide an in-depth analysis of node anonymity in three well-known complex network models. The proposed j-anonymity distributions can be used to measure disclosure probabilities\, which in turn can be used to assess disclosure risk. Numerical experiments reveal that many nodes are de-anonymized when their neighbourhood of radius 2 is known.
URL:https://www.popnet.io/events/10320-measuring-anonymity-in-complex-networks/
CATEGORIES:Conference talk
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/07/Networks-2021.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210623T173500
DTEND;TZID=Europe/Amsterdam:20210623T175500
DTSTAMP:20260503T115933
CREATED:20210630T114312Z
LAST-MODIFIED:20211029T100408Z
UID:516-1624469700-1624470900@www.popnet.io
SUMMARY:The Anatomy of Metropolitan Spatial Social Networks at Netstructure 21 satellite
DESCRIPTION:Lecture by Eszter Bokányi on Netstructure21 satellite \n\n\n\nSpatially embedded social networks have long been at the focus of researchers\, but the resolution of most studies was not enough to analyze how connections are formed within large urban areas\, and how all this is linked to the socio-economic status of people within the network. First\, I am going to show how commuting distance conditions the online social ties of Twitter users in the 50 largest metropolitan areas of the United States. Home and work locations are identified from geolocated tweets that enable us to infer the socio-economic status of individuals. The results suggest that commuting-enabled mixing manifests in reduced levels of income assortativity in online social relationships suggesting a universal role of commuting in integrating disparate social networks in cities. Second\, I am going to talk about the difference between the spatial concentration of social ties around people’s home and work locations\, and how the concentration around the home locations is stronger for people with lower socio-economic status\, whereas higher status users have a higher social connection density around their workplaces. These differences between the poor and the rich can also be observed in certain structural metrics of the ego-networks linked to social capital such as the clustering coefficient and the share of supported ties. This suggests that the structure of social networks around homes provide greater social capital for poor users than for rich users.
URL:https://www.popnet.io/events/the-anatomy-of-metropolitan-spatial-social-networks/
CATEGORIES:Conference talk
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/06/Netstructure21-satellite.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210615T130000
DTEND;TZID=Europe/Amsterdam:20210615T143000
DTSTAMP:20260503T115933
CREATED:20210609T082811Z
LAST-MODIFIED:20220113T123135Z
UID:460-1623762000-1623767400@www.popnet.io
SUMMARY:POPNET Connects with Zoltán Elekes
DESCRIPTION:Using Swedish register data for regional and network science \n\n\n\nDrawing on statistical registers\, Sweden offers world-class microdata resources for quantitative research. The register data covers the entire population of Sweden in a panel structure\, also matching workers to workplaces. As such it provides detailed information on individuals\, workplaces\, firms and regions over time. In this talk I will give an overview of the use of this dataset\, and provide examples of ongoing research based on it in the context of regional and network science. This part will first cover inferring coworker networks to explain individual\, firm and regional outcomes. Second\, I will show how constructing skill-relatedness networks enables the study of individual wage-mobility\, the economic resilience of local labour markets\, and helps informing regional policy on economic diversification. \n\n\n\nAbout Zoltan Elekes \n\n\n\nZoltán Elekes is engaged in research on topics at the intersection of evolutionary economic geography and network science. He holds a PhD in economics from the Doctoral School of Economics\, University of Szeged\, Hungary since 2018. In his thesis he explored how multinational enterprises and import influence the economic diversification of microregions. He is a research fellow at the ANET Lab of the Centre for Economic and Regional Studies in Hungary\, where he studies the geography of collaborative knowledge production and supplier-buyer networks. He leads a research project at the Centre for Regional Science at Umeå University\, Sweden on how the network structure of local labour markets condition regional economic resilience. He has published in leading field journals including Regional Studies and European Planning Studies\, and has refereed for Economic Geography and Regional Studies among others. Zoltán is the 2019 recipient of the Excellent Young Regional Scientist Award of the Hungarian Regional Science Association\, the Hungarian section of ERSA. Since 2019 he has been engaged on multiple occasions in consulting policymakers in Swedish regions on smart specialization and regional economic development. He continues to mentor students in Hungary\, and contributes to the Network and Spatial Analysis course developed by the ANET Lab. \n\n\n\nAbout POPNET Connects \n\n\n\nPOPNET Connects is the seminar series of the Population Scale Network Analysis (POPNET) platform. We invite everyone to join the seminar\, connect with others and get involved in discussion. Interested in joining? Send us an email or sign up for our mailing list.
URL:https://www.popnet.io/events/popnet-connects-with-zoltan-elekes/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/08/POPNET-Connects-v1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210518T130000
DTEND;TZID=Europe/Amsterdam:20210518T143000
DTSTAMP:20260503T115933
CREATED:20210517T063808Z
LAST-MODIFIED:20220113T123103Z
UID:387-1621342800-1621348200@www.popnet.io
SUMMARY:POPNET Connects with Yuliia Kazmina
DESCRIPTION:Uncovering corruption risks in public procurement using big data: the case of Ukraine \n\n\n\nCorruption\, favoritism and lack of public accountability have long been a central topic in academic research and policy debates. This study focuses on the phenomenon of corruption in a bureaucratic context\, in one of the most corruption-prone sectors – public procurement. In their attempts to fight institutionalized grand corruption\, governments all over the world improve the regulatory frameworks to ensure transparent and efficient public procurement market. One of the recent developments in the field was a successful launch of the ProZorro public procurement platform in Ukraine that achieved recognition all over the world as one of the best procurement reforms. Despite the enormous effort invested in the development of the transparent and efficient public procurement platform\, it is too early to conclude that ProZorro successfully eliminated corruption. Hence\, this study sets out to precisely estimate the prevalence and distribution of corruption risks in ProZorro. Overall\, we find that ProZorro faces issues related to the lack of competition such as a low number of suppliers and a high share of single bidding contracts in some of the procurement markets. To tackle these issues\, we develop a risk assessment tool for policymakers that could signal higher corruption risks in tendering processes. \n\n\n\nAbout Yuliia Kazmina \n\n\n\nYuliia Kazmina is a PhD Candidate at the POPNET project. She obtained a master’s degree in Economic Policy in Global Markets from the Central European University\, Hungary.Yuliia’s research interests concern the domain of computational social science and data-driven policymaking with a focus on network science approach. Previously Yuliia has been a data scientist at a think tank researching and advocating good governance and her policy projects focused on issues of transparency\, corruption\, and collusion in public funds as well as risks of organized crime.
URL:https://www.popnet.io/events/popnet-connects-with-yuliia-kazmina/
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/08/POPNET-Connects-v1.png
END:VEVENT
BEGIN:VEVENT
DTSTART;TZID=Europe/Amsterdam:20210429T140000
DTEND;TZID=Europe/Amsterdam:20210429T150000
DTSTAMP:20260503T115933
CREATED:20210423T090227Z
LAST-MODIFIED:20220113T123021Z
UID:222-1619704800-1619708400@www.popnet.io
SUMMARY:POPNET Connects with Eszter Bokányi
DESCRIPTION:Thursday 29th April 2021 from 14:00 – 15:00Seminar \nThe anatomy of metropolitan spatial social networks\nSpatially embedded social networks have long been at the focus of researchers\, but the resolution of most studies was not enough to analyze how connections are formed within large urban areas\, and how all this is linked to the socio-economic status of people within the network. First\, I am going to show how commuting distance conditions the online social ties of Twitter users in the 50 largest metropolitan areas of the United States. Home and work locations are identified from geolocated tweets that enable us to infer the socio-economic status of individuals. The results suggest that commuting-enabled mixing manifests in reduced levels of income assortativity in online social relationships suggesting a universal role of commuting in integrating disparate social networks in cities. Second\, I am going to talk about the difference between the spatial concentration of social ties around people’s home and work locations\, and how the concentration around the home locations is stronger for people with lower socio-economic status\, whereas higher status users have a higher social connection density around their workplaces. These differences between the poor and the rich can also be observed in certain structural metrics of the ego-networks linked to social capital such as the clustering coefficient and the share of supported ties. This suggests that the structure of social networks around homes provide greater social capital for poor users than for rich users. \nAbout Eszter Bokányi\nEszter Bokányi is a research postdoc in the POPNET project investigating a population-scale longitudinal 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 such as the spreading of innovations over these social networks.\n \n \n\n\nAbout POPNET Connects\n\n\n\nPOPNET Connects is the seminar series of the Population Scale Network Analysis (POPNET) platform. We invite everyone to join the seminar\, connect with others and get involved in discussion.
URL:https://www.popnet.io/events/popnet-connects-with-eszter-bokanyi/
LOCATION:Online
CATEGORIES:Seminar
ATTACH;FMTTYPE=image/png:https://www.popnet.io/wp-content/uploads/2021/08/POPNET-Connects-v1.png
END:VEVENT
END:VCALENDAR