Research

The NEtwoRks, Data, and Society (NERDS) group, founded in April 2019, is researching network and data science applications to social systems. NERDS consists of interdisciplinary researchers who focus on quantitative projects at the boundary of network science, data science, and computational social science, including science of science, social networks and dynamics, multiplex networks, science of success, urban sustainability, human mobility, data visualization, and fundamental questions in complex systems.

NERDS research stream

2020

J. HuangA.J. Gates, R. Sinatra, A.-L. Barabási
Historical comparison of gender inequality in scientific careers across countries and disciplines
Proceedings of the National Academy of Sciences USA (in print, 2020)

2019

B. Resch, M. Szell
Human-Centric Data Science for Urban Studies
ISPRS International Journal of Geo-Information 8, 584 (2019)

M. Coscia, L. Rossi
The Impact of Projection and Backboning on Network Topologies
ASONAM 2019

M. Coscia
Discovering Communities of Community Discovery
ASONAM 2019

Y. Yoshimura, R. Sinatra, A. Krebs, C. Ratti
Analysis of visitors’ mobility patterns through random walk in the Louvre Museum
Journal of Ambient Intelligence & Humanized Computing (AIHC), 1-16 (2019)

F. Giglietto, N. Righetti, G. Marino, L. Rossi
‘Fake news’ is the invention of a liar: How false information circulates within the hybrid news system
Current Sociology (2019)

F. Giglietto, N. Righetti, G. Marino, L. Rossi
Multi-Party Media Partisanship Attention Score. Estimating Partisan Attention of News Media Sources Using Twitter Data in the Lead-up to 2018 Italian Election
Comunicazione politica 1 (2019)

Foundational NERDS research

Our most important, defining works are:

S.P. Fraiberger, R. Sinatra, M. Resch, C. Riedl, A.-L. Barabási
Quantifying reputation and success in art 
Science, 362, 825-829 (2018)

C. Neumayer, L. Rossi
Images of protest in social media: Struggle over visibility and visual narratives
New Media & Society 20 (11), 4293-4310 (2018)

M. Coscia, F. Neffke
Network backboning with noisy data
IEEE 33rd International Conference on Data Engineering (ICDE), 425-436 (2017)

R. Sinatra, D. Wang, P. Deville, C. Song, and A.-L. Barabási
Quantifying the evolution of individual scientific impact
Science, 354, 6312 (2016)

P. Santi, G. Resta, M. Szell, S. Sobolevsky, S. Strogatz, C. Ratti
Quantifying the benefits of vehicle pooling with shareability networks
Proceedings of the National Academy of Sciences 111(37), 13290-13294 (2014)

M. Coscia, G. Rossetti, F. Giannotti, D. Pedreschi
Demon: a local-first discovery method for overlapping communities
Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining (2012)

M. Magnani, L. Rossi
The ml-model for multi-layer social networks
IEEE, Proceeding of 2011 International Conference on Advances in Social Networks Analysis and Mining (2011)

M. Szell, R. Lambiotte, S. Thurner
Multirelational organization of large-scale social networks in an online world
Proceedings of the National Academy of Sciences USA 107(31), 13636-13641 (2010)