POPNET

Income of home neighbourhood and the structure and concentration of online social ties in US metro areas
2021-07-28 10:45 - 11:00 (Europe/Amsterdam)
Conference talk at IC2S2

Authors: Sándor Juhász, Ádám Kovács, Balázs Lengyel and Eszter Bokányi

ABSTRACTThis study shows that online social connections of people in poor neighbourhoods are more spatially concentrated and structurally cohesive than the network of people living in better-off areas of the top 50 metropolitan areas of the US.

The effect of commuting on the income assortativity of social network ties
2021-07-28 09:45 - 10:00
Conference talk at IC2S2

Authors: Eszter Bokanyi, Sándor Juhász, Márton Karsai and Balazs Lengyel

ABSTRACTIn 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.

The community structure of global scientific collaboration - lecture at Networks2021 conference
2021-07-09 16:15 - 16:30
Lecture by Frank Takes on the Networks 2021 conference

Authors: Hanjo Boekhout; Eelke Heemskerk; Frank Takes

In 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.

Measuring Anonymity in Complex Networks at Networks 2021 conference
2021-07-06 20:45 - 21:00
Lecture by Rachel de Jong at Networks2021 conference

Authors: Rachel de Jong; Mark van der Loo; Frank Takes

Complex 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].

This 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.

This 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.

The Anatomy of Metropolitan Spatial Social Networks at Netstructure 21 satellite
2021-06-23 17:35 - 17:55
Lecture by Eszter Bokányi on Netstructure21 satellite

Spatially 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.

POPNET Connects with Zoltán Elekes
2021-06-15 13:00 - 14:30
Using Swedish register data for regional and network science

Drawing 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.

About Zoltan Elekes

Zoltán 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.

About POPNET Connects

POPNET 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.

POPNET Connects with Yuliia Kazmina
2021-05-18 13:00 - 14:30
Uncovering corruption risks in public procurement using big data: the case of Ukraine

Corruption, 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.

About Yuliia Kazmina

Yuliia 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.

POPNET Connects with Eszter Bokányi
2021-04-29 14:00 - 15:00 | Online
Thursday 29th April 2021 from 14:00 – 15:00Seminar
The anatomy of metropolitan spatial social networks
Spatially 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.
About Eszter Bokányi
Eszter 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.

About POPNET Connects

POPNET 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.
