Category Archives: Publication

The Atlas for the Aspiring Network Scientist

In the past two years,  NERDS member Michele Coscia has been working on a textbook for the Network Analysis class he teaches at ITU. This “Atlas for the Aspiring Network Scientist”, has now reached version 1.0, and 760 pages, and is available for anyone to read for free: https://arxiv.org/abs/2101.00863

Website: https://www.networkatlas.eu/

The Atlas aims at being broad, not deep, to be a pointer to the things you need to know about Network Science rather than a deep explanation of those things.

Consider this a v1.0 of a continuous effort. There are many things to improve: language, concepts, references, figures. Please contact Michele with any comments.

Michele also plans to have interactive figures on the website in the future. Version 1.0 was all financed using his research money and time. For the future, Michele will need some support to do this in his free time. If you feel like encouraging this effort, you can consider becoming a member on Patreon.

Find a more detailed explanation of The Atlas for the Aspiring Network Scientist on Michele’s page: https://www.michelecoscia.com/?p=1913

Two NERDS December papers

We have published two new papers in December:

  1. The Node Vector Distance Problem in Complex Networks, by M. Coscia, A. Gomez-Lievano, F. Neffke, published in ACM Computing Surveys

    The paper develops a new measure to quantify the distances between sets of nodes, with important applications on network dynamics such as spread of diseases.
    Read Michele’s blog post about it: https://www.michelecoscia.com/?p=1898
  2. Data-driven strategies for optimal bicycle network growth, by L.G. Natera Orozco, F. Battiston, G. Iniguez, M. Szell, published in Royal Society Open Science

    Here we investigate the network structure of bicycle networks in cities around the world, and find that they consist of hundreds of disconnected patches, even in cycling-friendly cities like Copenhagen. To connect these patches, we develop and apply data-driven, algorithmic network growth strategies, showing that small but focused investments allow to significantly increase the connectedness and directness of urban bicycle networks.

Four new summer papers by NERDS

We have published four new papers over the summer:

  1. New and atypical combinations: An assessment of novelty and interdisciplinarity, by M. Fontana, M. Iori, F. Montobbio, R. Sinatra, published in Research Policy

    We compare different indicators of novelty and interdisciplinarity, and find that often they can’t distinguish novel and non-novel articles apart. We also find measured novelty highly overlaps measured interdisciplinarity, because the two are operationalized in similar ways.
  2. Mapping socioeconomic indicators using social media advertising data, by M. Fatehkia, I. Tingzon, A. Orden, S. Sy, V. Sekara, M. Garcia-Herranz, I. Weber, published in EPJ Data Science

    In this paper we ask: Is it possible to estimate poverty using data from the Facebook Ad platform?
  3. Knowledge diffusion in the network of international business travel, by M. Coscia, F.M.H. Neffke, R. Hausmann, published in Nature Human Behavior

    Read Michele’s blog post about it: http://www.michelecoscia.com/?p=1838
  4. Multiplex Graph Association Rules for Link Prediction, by M. Coscia and M. Szell, accepted for publication in 15th International Conference on Web and Social Media (ICWSM) 2021

    Here we investigate the multiplex link prediction problem with graph association rules: Will two nodes connect, and of which type?

Back from lockdown with 2 papers

NERDS are back from the lockdown with two three new papers published today:

  1. Distortions of political bias in crowdsourced misinformation flagging, by Michele Coscia and Luca Rossi, published in the Journal of the Royal Society Interface

    Luca writes more about the paper here: https://blogit.itu.dk/lucarossi/2020/06/10/reasonable-wrong-technical-solutions-to-social-problems/
    And here Michele’s take: http://www.michelecoscia.com/?p=1816

  2. Extracting the multimodal fingerprint of urban transportation networks, by Luis Guillermo Natera Orozco, Federico Battiston, Gerardo Iñiguez, and Michael Szell, published in Transport Findings

    In this paper we analyze urban transport network layers of multiple cities and come up with a multiplex-network based method to construct a “fingerprint” of how these layers connect. This gives insights and a classification on the multimodal potential of cities (how their modes of transport are connected).

Update June 11th: Make that one more:

3. Generalized Euclidean Measure to Estimate Network Distances, by Michele Coscia, published in ICWSM-2020