Roberta became co-lead in the AI Pioneer Centre

Yesterday Denmark’s new Pioneer Center for Artificial Intelligence was opened ceremonially, where Roberta took part in a panel discussion. Roberta’s role in the centre will be the new co-load of the Networks and Graphs Collaboratory together with Sune Lehmann.

The Pioneer Centre for Artificial Intelligence focuses on fundamental research, and within an interdisciplinary framework, develops platforms, methods, and practices addressing society’s greatest challenges. It brings together world-class artificial intelligence research in Denmark.

We are excited to see the novel science the centre will enable and produce, and which opportunities it will bring for attracting more world-class research to the country.

Two NERDS papers out: Measuring Violence via Twitter and Missing Links in Bike Networks

We start the spring with two new papers:

    1. Measuring Violence: A Computational Analysis of Violence and Propagation of Image Tweets From Political Protest, by L. Rossi, C. Neumayer, J. Henrichsen, and L.K. Beck, published in Social Science Computer Review

      We investigated the impact of violence on the propagation of images in social media in the context of political protest. Using a computational approach, we measure the relative violence of a large set of images shared on Twitter during the protests against the G20 summit in Frankfurt am Main in 2017. This allows us to investigate if more violent content is shared more times and faster than less violent content on Twitter, and if different online communities can be characterized by the level of violence of the visual content they share. The level of violence in an image tweet does not correlate with the number of retweets and mentions it receives that the time to retweet is marginally lower for image tweets containing a high level of violence and that the level of violence in image tweets differs between communities.
    2. Automated Detection of Missing Links in Bicycle Networks, by A. Vybornova, T. Cunha, A. Gühnemann, and M. Szell, published in Geographical Analysis

      Here, we develop the IPDC procedure (Identify, Prioritize, Decluster, Classify) for finding the most important missing links in urban bicycle networks, using data from OpenStreetMap. In this procedure we first identify all possible gaps following a multiplex network approach, prioritize them according to a flow-based metric, decluster emerging gap clusters, and manually classify the types of gaps. We apply the IPDC procedure to Copenhagen and report the 105 top priority gaps. For evaluation, we compare these gaps with the city’s most recent Cycle Path Prioritization Plan and find considerable overlaps. Our results show how network analysis with minimal data requirements can serve as a cost-efficient support tool for bicycle network planning.
      We also developed an interactive visualization of our results at: fixbike.net

First NERDS papers of 2022 published: Epidemic Dreams and Conflicts versus Polarization

We start 2022 with two new papers!

    1. Epidemic dreams: dreaming about health during the COVID-19 pandemic, by S. Šćepanović, L.M. Aiello, D. Barrett and D. Quercia, published in Royal Society Open Science

      Luca and collaborators ask: Why were our dreams during the pandemic weird? Their computer analysis unearthed buried psychological reactions to the COVID-19 pandemic: expressions in waking life reflected a linear and logical thought process and, as such, described realistic symptoms or related disorders (e.g. nasal pain, SARS, H1N1); those in dreaming life reflected a thought process closer to the visual and emotional spheres and, as such, described either conditions unrelated to the virus (e.g. maggots, deformities, snake bites), or conditions of surreal nature (e.g. teeth falling out, body crumbling into sand).
    2. How minimizing conflicts could lead to polarization on social media: An agent-based model investigation, by M. Coscia and L. Rossi, published in PLOS ONE
       

       The paper explores an agent based model on how policing content and backlash on social media (i.e. conflict) can lead to an increase in polarization for both users and news sources. We find that the tendency of users and sources to avoid policing, backlash and conflict in general can increase polarization online. Specifically polarization comes from the ease of sharing political posts, intolerance for opposing points of view causing backlash and policing, and volatility in changing one’s opinion when faced with new information. On the other hand, it seems that the integrity of a news source in trying to resist the backlash and policing has little effect.
      Learn more on Michele’s blogpost.

Call for PhD scholarships by the Danish Data Science Academy

The new Danish Data Science Academy (DDSA), which we helped to establish, invites applications for ten three-year PhD scholarships for individual research projects within any field of data science, including all research topics pursued by NERDS. The DDSA encourages visionary and ambitious young data scientists to develop their own research projects with the assistance of a supervisor from a Danish university (like ITU).

See more information here: https://ddsa.dk/open-calls/open-call-for-phd-scholarships/
Deadline for application is 20 March 2022

Given that both our currently existing PhD students (Anastassia and Ane) were hired through similar calls, there is a good probability to make this also work out for future candidates. If your research interests overlap with ours and you are interested please get in touch with one of our assistant or associate professors to explore options to apply!

You will need to come up with your own research plan, but feel free to get inspired by our most recent master level project ideas: https://nerds.itu.dk/2021/09/01/research-project-market-2021/

 

 

Ane Rahbek Vierø has joined NERDS

Happy new year! 🥳

We are thrilled to welcome Ane Rahbek Vierø to our research group!

Ane joins us as PhD student for 3 years, funded by the Danish Ministry of Transport for an application which she authored, supported by her new supervisor Michael Szell. She completed her Master’s degree in 2020 from Lund University on a thorough analysis of Copenhagen’s bicycle network, and has been working since then as research assistant at Aalborg University. Her background is in Geographical Information Science which is a great complement for our existing NERDS expertise. She is also well connected in the Danish cycling research community, having co-organized the recent CRBAM21, which will additionally strengthen our research group’s connections within Denmark.

Given her professional expertise in bicycle network analysis, her GIS background and procedural approach via Python, and her past experience – such as an internship in the cycling development team of the municipality of Copenhagen – she is the perfect person to undertake this ambitious PhD project: Network analysis of the Danish cycling infrastructure.

Together with our PhD student Anastassia, who works on a very similar topic and who also joined recently, we anticipate an increasing output in cycling research in the coming years. Our goal is not just producing research papers, but more importantly to improve the Danish cycling landscape locally, and to provide general insights and methods towards a modal shift to sustainable transport on the global level. 

Luca Aiello wins Carlsberg Young Researcher Fellowships

Luca Aiello was one of the recipients of this year’s Carlsberg Young Researcher Fellowships.


The Carlsberg Young Researcher Fellowship funds three-year fellowships for newly appointed tenured associate professors to establish an independent research group and forming an international network.

Luca’s winning proposal was awarded with DKK 5M:
COCOONS: COllective COordination through ONline Social media

In the coming decades, a defining task for humanity will be to solve global challenges through mass coordination. The goal of the project is to unveil the prime elements of social interactions that enable spontaneous coordination in the face of social dilemmas. It will do so by quantifying fundamental dimensions of social interactions with Natural Language Processing algorithms applied to online social media conversations, and to leverage principles from complex systems science to find how these dimensions are linked to cooperation outcomes in social networks.

We are excited about Luca’s success and are looking forward to welcome one new PhD student and two postdocs that will be recruited starting October 2022. Stay tuned for upcoming job calls.

New group photos

Taking advantage of the still relatively relaxed pandemic situation in Denmark we finally all met up and took new group photos:

Taking these group photos was way overdue, since the last time we took one, in April 2019, we were only 4 members. Now we are 14, and growing soon again..

Establishing the Nightingale Network

Together with Sune Lehmann and Laura Alessandretti from SODAS/DTU we are establishing the Nightingale Network: The Nightingale Network brings together faculty, postdocs, and students based in Denmark who share an interest in Computational Social Science, Complex Systems, and Network Science.

More info and subscribe here: https://www.socialdatascience.dk/nightingale

We aim to strengthen the Denmark-based data and network science community, and send out a monthly newsletter listing relevant events, news, and job postings in Denmark and beyond. Please also share your tips, calls, and job postings!

We will also organize regular gatherings. The first event was the first Nightingale Network Night which happened last week at ITU, and which successfully established and strengthened many social and culinary connections, from Scaccia to Borek and Apfelstrudel:

We will also share the nerdy party games we created on our github page so that others can replicate the fun! https://github.com/NERDSITU/nerdyicebreakers

Sign up to our news, and see you soon (modulo lockdown)!

A dream come true for Luca Aiello 🖖

Our very own Luca Aiello was interviewed by none other than William “Captain Kirk” Shatner on his recent dreams research, in Shatner’s show “I Don’t Understand”:

https://www.rt.com/shows/i-don-t-understand-with-william-shatner/532878-dream-analysis-social-science/

Watch the 26 minute interview to see Luca baffling and exciting Shatner by answering his burning questions, such as:

What in heaven’s name is computational science doing with dreams?

What methodology did you use to give us an algorithm about dreams?

Say you meant to say “maybe” and you said “baby”, one would have said prior to your science “That was a Freudian slip” – you don’t work that way?

It could be Hitler all over again?

Could you understand why an individual does not take a vaccine?

No doubt this interview was a NERDS dream come true! 🖖

Two new NERDS papers: NFT market and Pearson correlations on networks

Two new papers from the NERDS crew!

    1. Mapping the NFT revolution: market trends, trade networks, and visual features, by M. Nadini, L. Alessandretti, F. Di Giacinto, M. Martino, L.M. Aiello, A. Baronchelli, published in Scientific Reports

      Luca and collaborators performed the first large-scale analysis of the market of Non Fungible Tokens (NFTs) since its birth. The looked at 6.1 million trades of 4.7 million NFTs to learn about market, traders, visual features and price prediction. The dataset they collected is available. Learn more on this blogpost from the Alan Turing Institute.
      Also, watch the accompanying video: https://www.youtube.com/watch?v=KyIITtPKJbY
    2. Pearson correlations on complex networks, by M. Coscia, published in Journal of Complex Networks
       

       
      Estimating the correlation between two processes happening on the same network is therefore an important problem with a number of applications. However, at present there is no way to do so: current methods to estimate the correlation between two processes happening on the same network either correlate a network with itself, a single process with the network structure, or calculate a network distance between two processes. To fill this gap, Michele created a new method to extend the Pearson correlation coefficient to work on complex networks, and showed its usefulness in tasks related to social network analysis and economics. Learn more on this blogpost.