New NERDS paper on COVID genome sequencing

Our newest faculty hire Jonas L. Juul is already making a splash. He published a big multi-author paper in Nature Communications: High-resolution epidemiological landscape from ~290,000 SARS-CoV-2 genomes from Denmark, by M.P. Khurana et al

We are happy that with Jonas, who was part of the Statens Serum Institut’s expert group on mathematical modeling of COVID-19 during the reopening of Denmark in the spring and summer of 2020, we have gained a solid footing in medical applications of data/network science.


We examined the drivers of molecular evolution and spread of 291,791 SARS-CoV-2 genomes from Denmark in 2021. With a sequencing rate consistently exceeding 60%, and up to 80% of PCR-positive samples between March and November, the viral genome set is broadly whole-epidemic representative. We identify a consistent rise in viral diversity over time, with notable spikes upon the importation of novel variants (e.g., Delta and Omicron). By linking genomic data with rich individual-level demographic data from national registers, we find that individuals aged  < 15 and  > 75 years had a lower contribution to molecular change (i.e., branch lengths) compared to other age groups, but similar molecular evolutionary rates, suggesting a lower likelihood of introducing novel variants. Similarly, we find greater molecular change among vaccinated individuals, suggestive of immune evasion. We also observe evidence of transmission in rural areas to follow predictable diffusion processes. Conversely, urban areas are expectedly more complex due to their high mobility, emphasising the role of population structure in driving virus spread. Our analyses highlight the added value of integrating genomic data with detailed demographic and spatial information, particularly in the absence of structured infection surveys.

Carlson Büth wins VCD Award for his Master thesis

Carlson Moses Büth, who visited us last year from University of Münster, Germany, won the VCD Award (1st place Special Award) for his master thesis

From Gridlocks to Greenways: Analyzing the Network Effects of Computationally Generated Low Traffic Neighborhoods

that he wrote at ITU, co-supervised by Anastassia+Michael@NERDS. We congratulate Carlson to this achievement! 🎉


Photos from the VCD Award Ceremony by Jan Zappner

The VCD is the “Verkehrsclub Deutschland”, a major non-profit association and traffic club in Germany that is committed to a socially and environmentally friendly transport transition towards mobility for all road users.

Over the course of his master thesis Carlson also initiated the development of the Python package superblockify which we published recently within the JUST STREETS EU Horizon project we are part of. See: superblockify.city, its Github repository, and the accompanying paper at JOSS.

New NERDS paper on network analysis of Italian music

A new NERDS authored paper is out in Applied Network Science: Node attribute analysis for cultural data analytics: a case study on Italian XX–XXI century music, by M. Coscia


We use the Italian music record industry from 1902 to 2024 as a case study. In this scenario, a possible research objective could be to discuss the relationships between different music genres as they are performed by different bands. Estimating genre similarity by counting the number of records each band published performing a given genre is not enough, because it assumes bands operate independently from each other. In reality, bands share members and have complex relationships. These relationships cannot be automatically learned, both because we miss the data behind their creation, but also because they are established in a serendipitous way between artists, without following consistent patterns. However, we can be map them in a complex network. We can then use the counts of band records with a given genre as a node attribute in a band network. In this paper we show how recently developed techniques for node attribute analysis are a natural choice to analyze such attributes. Alternative network analysis techniques focus on analyzing nodes, rather than node attributes, ending up either being inapplicable in this scenario, or requiring the creation of more complex n-partite high order structures that can result less intuitive. By using node attribute analysis techniques, we show that we are able to describe which music genres concentrate or spread out in this network, which time periods show a balance of exploration-versus-exploitation, which Italian regions correlate more with which music genres, and a new approach to classify clusters of coherent music genres or eras of activity by the distance on this network between genres or years.

NERDS at ASONAM’24

A bunch of nerds posing in front of the asonam conference logoLuigi Arminio wins the asonam best phd dissertation award

NERDS’ summer sheneanigans continue at ASONAM, in the beautiful and sunny Calabria. Lucio La Cava and Alessia Galdeman held a tutorial on Mining, Modeling, and Analyzing Decentralized Social Media. Alessia Antelmi organized the HyperSci workshop on Theory and Applications of Hypernetwork Science. Luigi Arminio and Daniele De Vinco presented at the PhD Forum. Luca Aiello fulfilled his duties as the conference Program Chair. Luigi won the prize for the best PhD forum contribution!

Claudia Acciai has joined NERDS

We are chuffed to welcome Claudia Acciai to our research group!

Claudia joins us as Postdoc, coming from the Department of Sociology at University of Copenhagen (KU), where she was working on quantifying institutional and country-related Matthew effects in science.

Her work lies at the intersection of comparative public policy, innovation studies and science of science. In her research she combines computational and experimental methods with qualitative content analysis techniques.

At NERDS she joins via the Villum Synergy project Quantifying the Prevalence and Diffusion of Generative AI in Science, supervised by Roberta Sinatra, collaborating closely also with the project’s second PI, Mathias Wullum Nielsen.

CFP Special Issue on Polarization on Social Networks

In collaboration with Prof. Matteo Magnani – InfoLab Uppsala University – some NERDS are editing a special issue of Network Science focusing on Polarization on Social Network.

Read the full call here. The submission deadline is March 31, 2025, but the articles will be processed as soon as submitted. We encourage  to send an abstract to the editors by October 31, to receive feedback about suitability of the proposal for the special issue.

Articles will be made available as soon as possible after acceptance, and later included into a special collection when all the submissions to this special issue have been processed.
Reach out if you want to discuss if an idea you have is suitable, otherwise just submit!

Welcome Lasse, the latest NERDS PhD Student!

NERDS keeps growing! This month we’re welcoming Lasse Alsbirk as our latest addition to the team!

Lasse is a co-financed PhD student and at the center of a multi-partnered research project! He will work at the intersection of the Danish Police (financial crimes section), the AI Pioneer Center, and NERDS @ ITU. His project will focus on the application and development of network science tools to fight financial crimes. He has valuable abroad experience, having received his master degree in Israel and he will be with us for four years.

Welcome, Lasse!

Three new NERDS papers with our master students: Failing our youngest, superblockify, women on wikipedia

We have 3 new papers that came out over the summer so far, on diverse, very interesting topics. The first authors in all 3 of these papers were our master students – showing how impactful good master projects can be:

  1. Failing Our Youngest: On the Biases, Pitfalls, and Risks in a Decision Support Algorithm Used for Child Protection, by T.M. Hansen, R. Sinatra, and V. Sekara, published at FAccT’24
    Through a freedom of information request, we accessed a new algorithm of Danish child protection services to aid caseworkers in identifying children at heightened risk of maltreatment, named Decision Support, and conduct an audit. We find that the algorithm has significant methodological flaws, suffers from information leakage, relies on inappropriate proxy values for maltreatment assessment, generates inconsistent risk scores, and exhibits age-based discrimination. Given these serious issues, we strongly advise against the use of this kind of algorithms in local government, municipal, and child protection settings, and we call for rigorous evaluation of such tools before implementation and for continual monitoring post-deployment by listing a series of specific recommendations.

    See also our accompanying policy paper published earlier.
  2. superblockify: A Python Package for Automated Generation, Visualization, and Analysis of Potential Superblocks in Cities, by C.M. Büth, A. Vybornova, and M. Szell, published in The Journal of Open Source Software (JOSS)
    superblockify is a Python package designed to assist in planning future Superblock implementations by partitioning an urban street network into Superblock-like neighborhoods and providing tools for visualizing and analyzing these partition results. A Superblock is a set of adjacent urban blocks where vehicular through traffic is prevented or pacified, giving priority to people walking and cycling. The potential Superblock blueprints
    and descriptive statistics generated by superblockify can be used by urban planners as a first step in a data-driven planning pipeline for future urban transformations, or by urban data scientists as an efficient computational method to evaluate potential Superblock partitions.


    The software is available at: superblockify.city
  3. Traces of Unequal Entry Requirement for Illustrious People on Wikipedia Based on their Gender, by L. Krivaa and M. Coscia, published in Advances in Complex Systems
    In this paper, we study issues of fair gender representations for people in history noted by multiple language editions of Wikipedia: are women underrepresented on Wikipedia? We do so via a combination of natural language processing and network science. Our results indicate that there is indeed a higher bar for women to have their own biographical page on Wikipedia: women are only included when they have more significant connections than men to the rest of the network. There are visible effects of the initiatives Wikipedia is taking to fix this issue, showing that the gap is narrowing, which validates our interpretation of the data.

Jonas L. Juul has joined NERDS

We are thrilled to welcome Jonas L. Juul to our research group!

Jonas joins us as Assistant Professor, after an illustrious past in network science, having worked -among others- with Mason Porter, Steven Strogatz, Jon Kleinberg, and Sune Lehmann *hashtag namedrop*. He uses statistical methods, mathematical modeling and computer simulations to study social networks, spreading processes and human behavior. Recently, he has been particularly interested in how content spreads between online users, and how to mitigate the spread of diseases in human populations. He approaches these questions both empirically — using methods from modern data science — and theoretically with methods from physics and mathematical modeling.

Jonas had past professional roles at Technical University of Denmark and Cornell University, and he was also part of the Statens Serum Institut’s expert group on mathematical modeling of COVID-19 during the reopening of Denmark in the spring and summer of 2020. Check out Jonas’ cool Webpage to find more information about him.

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!