NERDS at IC2S2’24 in Philly!

A tactical squad of 6 NERDS attended this year’s IC2S2 in Philly, and presented 9 works:

We are grateful to the organizers for the great event, and we look forward to IC2S2 coming back to scandinavia in 2025!

New NERDS paper on urban morphology & street network simplification

A new NERDS co-authored paper is out open-access in the Journal of Spatial Information Science (JOSIS): A shape-based heuristic for the detection of urban block artifacts in street networks, by Martin Fleischmann & Anastassia Vybornova.

a) Bridge, Amsterdam; b) Roundabout, Abidjan; c) Intersection, Kabul; d) Motorway, Vienna. Polygons classified as face artifacts are shown in red, and the OSM street network (without service roads) is shown in black. Face artifacts are polygons enclosed by street network geometries (in the case of OSM, lane centerlines) that do not represent morphological urban blocks, but instead are a result of detailed transportation-focused mapping of the streetscape. Map data (c) OpenStreetMap contributors (c) CARTO

a) Bridge, Amsterdam; b) Roundabout, Abidjan; c) Intersection, Kabul; d) Motorway, Vienna. Polygons classified as face artifacts are shown in red, and the OSM street network (without service roads) is shown in black. Face artifacts are polygons enclosed by street network geometries (in the case of OSM, lane centerlines) that do not represent morphological urban blocks, but instead are a result of detailed transportation-focused mapping of the streetscape. Map data (c) OpenStreetMap contributors (c) CARTO

We propose a cheap computational heuristic for the identification of ‘face artifacts’, i.e., geometries that are enclosed by transportation edges but do not represent urban blocks. Sounds cryptic? Just check out the picture – the artifacts (in red) might be painfully familiar to anyone who has worked with street network data. Our proposed heuristic, implemented open-source in momepy, is the first step towards a fully automated street network simplification workflow. Next steps coming up – stay tuned!

NERDS at ICWSM’24

This week, Arianna and Anders are representing NERDS at ICWSM in Buffalo, NY, with two freshly-published papers.

  1. Narratives of Collective Action in YouTube’s Discourse on Veganism, by A. Pera and L.M. Aiello. ICWSM’24.

    We studied vegan narratives on YouTube through the lens of a theoretical framework of moral narratitves. We studied how different narratives elicit different types of responses from video commenters, and found that videos advocating social activism are the most effective at stirring reactions marked by heightened linguistic markers that relate to collective action.
  2. The Persuasive Power of Large Language Models by A.G. Møller and L.M. Aiello. ICWSM’24.

    Can artificial agents interact with each other to reproduce human-like persuasive dialogue? And do the arguments they generate sound persuasive to humans? We used Llama2 to test different persuasion strategies, and asked humans to rate them. We found that arguments that included factual knowledge, markers of trust, expressions of support, and conveyed status were deemed most effective according to both humans and agents.

NERDS at Como Summer School and WebSci’24

Arianna and Anders participated to the first editions of the Computational Social Science Summer School in Como, presenting their work on the COCOONS project. Arianna, Daniele, and external collaborator Maddalena Torricelli also attended the WebSci conference in Stuttgard, presenting an analysis of climate action communication on TikTok [paper], the use of hypergraphs to model opinion dynamics in large-scale social media [poster], and the role of interfaces in shaping human creativity during the interaction with generative AI tools [paper].

New NERDS paper out on Machine Learning in Humanitarian Work

We published a new paper:

THE OPPORTUNITIES, LIMITATIONS, AND CHALLENGES IN USING MACHINE LEARNING TECHNOLOGIES FOR HUMANITARIAN WORK AND DEVELOPMENT, by V. Sekara, M. Karsai, E. Moro, D. Kim, E. Delamonica, M. Cebrian, M. Luengo-Oroz, R. Moreno Jimenez, M. Garcia-Herranz, published in Advances in Complex Systems

Novel digital data sources and tools like machine learning (ML) and artificial intelligence (AI) have the potential to revolutionize data about development and can contribute to monitoring and mitigating humanitarian problems. The potential of applying novel technologies to solving some of humanity’s most pressing issues has garnered interest outside the traditional disciplines studying and working on international development. Today, scientific communities in fields like Computational Social Science, Network Science, Complex Systems, Human Computer Interaction, Machine Learning, and the broader AI field are increasingly starting to pay attention to these pressing issues. However, are sophisticated data driven tools ready to be used for solving real-world problems with imperfect data and of staggering complexity? We outline the current state-of-the-art and identify barriers, which need to be surmounted in order for data-driven technologies to become useful in humanitarian and development contexts. We argue that, without organized and purposeful efforts, these new technologies risk at best falling short of promised goals, at worst they can increase inequality, amplify discrimination, and infringe upon human rights.

Postdoc wanted for analyzing networks of the Roman Empire

We are looking for a postdoc to work on a cool multidisciplinary project on networks and the Roman Empire ⚔️, at the NERDS (NEtwoRks, Data, and Society) research group at IT University of Copenhagen. Apply here if interested (deadline May 23rd)! 

In the project, you will be expected to develop network analysis techniques to work with extremely incomplete and heavily biased archaeological data. The idea is to try to reconstruct social relationships between different places in the Roman Empire. We are going to integrate remains at various sites with the most detailed to date reconstruction of Roman mobility. Check out this cool Roman roads network picture. That’s the stuff you’re going to work with!

The work is part of a Villum Synergy project. You’ll be supervised directly by Michele Coscia. You will interact on a regular basis with a team of cool archaeologists from Aarhus University, headed by Tom Brughmans.

Here’s the link to read more about the call and apply (deadline May 23rd): https://candidate.hr-manager.net/ApplicationInit.aspx?cid=119&ProjectId=181689&DepartmentId=3439&MediaId=1282

The NERDS group is a down-to-earth and fun place to be. Copenhagen is often named as the best city in the world to live in, and for good reasons. It’s world-renowned for food, beer, art, music, architecture, the Scandinavian “hygge”, and much more. In Denmark, parental leave is generous, and child-care is excellent and cheap.

New NERDS paper out on success in tennis

We published a new multi-NERDS paper, concluding a successful previous internship of Chiara Zappalà!

Early career wins and tournament prestige characterize tennis players’ trajectories, by C. Zappalà, S. Sousa, T. Cunha, A. Pluchino, A. Rapisarda and R. Sinatra, published in EPJ Data Science


We study the unfolding of tennis players’ careers to understand the role of early career stages and the impact of specific tournaments on players’ trajectories. We employ a comprehensive approach combining network science and analysis of the Association of Tennis Professionals (ATP) tournament data and introduce a novel method to quantify tournament prestige based on the eigenvector centrality of the co-attendance network of tournaments. Focusing on the interplay between participation in central tournaments and players’ performance, we find that the level of the tournament where players achieve their first win is associated with becoming a top player. This work sheds light on the critical role of the initial stages in the progression of players’ careers, offering valuable insights into the dynamics of success in tennis.

5 years of NERDS!

NERDS was founded 5 years ago by three young assistant professors and one associate professor, to be a reference point at ITU for the research on network and data science applications to social systems. At 5 years old, we have learned to write our name (we have a logo), to follow rules, and to use a fork and knife for eating. And hoo boy, did we use that fork last friday when celebrating our anniversary with an original NERDS cake!

We also got new group photos taken (by Sebastian Mateos Nicolajsen – thx!), see below, because we have grown to 20+ members over the years! For all bean counting aficionados, we also won over 5M EUR of research funding and published 84 papers so far.

Further highlights, shown in the timeline above. We:

Looking back to our goals 5 years ago, we have all reason to be proud to have 1) built up a flourishing network of Denmark-based network/data science research groups, connecting ITU, KU, DTU, and others, 2) successfully impressed several funding agencies and public stakeholders to engage with us solving societal problems with our research. We will continue along this road, developing further our group in a safe and fun environment.

In our near future, we look forward to welcoming several new group members in the fall, including one assistant professor and several PhDs/Postdocs.

Live long and prosper 🖖
Luca, Luigi, Roberta, Claudia, Anastassia, Jacob, Vedran, Sandro, Anders, Michele, Anders 2, Ane, Toine, Mesut, Luca 2, Michael, Arianna, Clement, Elisabetta, Alessia, Jacopo, Daniele, Nicoló

Mesut Kaya has joined NERDS

We are happy to welcome Mesut Kaya to our research group!

Mesut joins us as an Industrial Postdoc funded by the Innovation Fund. Previously, Mesut was at Aalborg University Copenhagen; before in Delft University and University College Cork. Mesut works on recommender systems in general, at NERDS he will be working with Toine Bogers specifically on recommendation in the HR domain: job recommendation, candidate recommendation, and now the fairness of algorithmic hiring in general.

New NERDS paper out on bicycle network quality in Denmark

We published a new all-NERDS paper, applying our BikeDNA tool to the whole country of Denmark as part of our Cykelpulje project!

How Good Is Open Bicycle Network Data? A Countrywide Case Study of Denmark, by A. Rahbek Vierø, A. Vybornova, and M. Szell, published in Geographical Analysis


We compare the two largest open data sets on dedicated bicycle infrastructure in Denmark, OpenStreetMap (OSM) and GeoDanmark, in a countrywide data quality assessment, asking whether the data are good enough for network-based analysis of cycling conditions. We find that neither of the data sets is of sufficient quality, and that data conflation is necessary to obtain a more complete data set. Our analysis of the spatial variation of data quality suggests that rural areas are more prone to incomplete data. We demonstrate that the prevalent method of using infrastructure density as a proxy for data completeness is not suitable for bicycle infrastructure data, and that matching of corresponding features is thus necessary to assess data completeness. Based on our data quality assessment, we recommend strategic mapping efforts toward data completeness, consistent standards to support comparability between different data sources, and increased focus on data topology to ensure high-quality bicycle network data.

Explore also the interactive map: https://anerv.github.io/bikedna_webmap/