Network performance

how groups coordinate, seek knowledge, optimize and reach success

This work focuses on the social dynamics of knowledge exchange and learning that drive collaboration, collective intelligence, and discovery. Most problem-solving tasks are carried out in group or team settings, and require complex interactions that involve cognitive, social and informational exchange. The goal is to develop rigorous models and techniques to understand how groups reach consensus, achieve breakthroughs, and perform in groups.

Featured publications

A structural transition in physical networks

Nima Dehmamy, Soodabeh Milanlouei & Albert-László Barabási
Nature
November 28, 2018

Measurability of the epidemic reproduction number in data-driven contact networks

Quan-Hui Liu, Marco Ajelli, Alberto Aleta, Stefano Merler, Yamir Moreno, and Alessandro Vespignani
PNAS
November 21, 2018

Network integration of multi-tumour omics data suggests novel targeting strategies

Ítalo Faria do Valle, Giulia Menichetti, Giorgia Simonetti, Samantha Bruno, Isabella Zironi, Danielle Fernandes Durso, José C. M. Mombach, Giovanni Martinelli, Gastone Castellani & Daniel Remondini
Nature Communications
October 30, 2018

Recent publications

Scale-free Networks Well Done

Ivan Voitalov, Pim van der Hoorn, Remco van der Hofstad, and Dmitri Krioukov
Phys. Rev. Research
October 18, 2019

The chaperone effect in scientific publishing

Vedran Sekara, Pierre Deville, Sebastian E. Ahnert, Albert-László Barabási, Roberta Sinatra, and Sune Lehmann
PNAS
December 11, 2018

A structural transition in physical networks

Nima Dehmamy, Soodabeh Milanlouei & Albert-László Barabási
Nature
November 28, 2018

Measurability of the epidemic reproduction number in data-driven contact networks

Quan-Hui Liu, Marco Ajelli, Alberto Aleta, Stefano Merler, Yamir Moreno, and Alessandro Vespignani
PNAS
November 21, 2018

The Formula: The Universal Laws of Success

Albert-László Barabási
Little, Brown and Company
November 6, 2018

Featured news coverage

Why Experts Reject Creativity

The Atlantic, October 2014

Featured project

The Science of Success project focuses on developing measures and methods to model and predict success in a range of settings that have quantifiable indicators of performance (e.g., science, sports, software development). Driven by the hypothesis that success is not an individual phenomenon, but rather a collective one, we use large-scale data sets to identify patterns of career paths, individual and team performance, and the dynamics of impact and attribution. Findings offer actionable information towards a quantitative evaluation of success in a diverse range of competitive settings, from science to sports to software development.

Major funders

DARPA, Army Research Office, AFOSR