Author Archives: luai

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.

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.