Andrea Baronchelli

I am a Professor of Complexity Science at City, University of London, and also the Token Economy theme lead at The Alan Turing Institute and a Research Associate at the UCL Centre for Blockchain Technologies.

I study human behaviour and self-organisation in decentralised socio-technical systems. I use complex systems, network science, and machine learning to analyse large datasets, create mathematical models, and conduct experiments with human subjects.

My research has advanced our knowledge of topics such as coordination in complex networks, cryptocurrency and blockchain ecosystems, information spread and polarization in social networks, social norm emergence, human categorization, collective behaviour tipping points, human mobility, and network science fundamentals (diffusion processes and temporal networks).

My work has been published in top journals like Science, PNAS, Nature Human Behaviour, Nature Climate Change, Nature Communications, Science Advances, and Physical Review Letters. It has received support from various organizations, including UKRI, PayPal, ESRC, InnovateUK, and the UK Government. In 2019, I received the Young Scientist Award for Socio and Econophysics from the German Physical Society.

Mapping the NFT revolution

The paper Mapping the NFT revolution: market trends, trade networks, and visual features (Oct '21) presented the first comprehensive analysis of the NFT phenomenon.

Critical mass and tipping points in social convention

I have been researching the dynamics of norm formation and collective behaviour change for more than 15 years.

IC2S2'20 Keynote talk

Collective Dynamics of Dark Web Marketplaces

Together with academic and industrial partner we analyse and model licit and illicit trade networks

ACM Collective Intelligence '20

Selected publications:

Growing polarization around climate change on social media. Nature Climate Change (2022)
Macroscopic properties of buyer–seller networks in online marketplaces. PNAS Nexus (2022)
Central bank digital currencies risk becoming a digital Leviathan. Nature Human Behaviour (2022)
Mapping the NFT revolution: market trends, trade networks and visual features. Scientific Reports (2021)
Experimental evidence for scale-induced category convergence across populations. Nature Communications (2021)
From code to market: Network of developers and correlated returns of cryptocurrencies. Science Advances (2020)
The emergence of consensus. Royal Society Open Science (2018)
The dynamics of norm change in the cultural evolution of language. PNAS (2018)
Experimental evidence for tipping points in social convention. Science (2018)
Evidence for a conserved quantity in human mobility. Nature Human Behaviour (2018)
Evolutionary dynamics of the cryptocurrency market. RSOS (2017)
The spontaneous emergence of conventions: An experimental study of cultural evolution. PNAS (2015)
Networks in Cognitive Science. Trends Cog. Sci. (2013)
Modeling human dynamics of face-to-face interaction networks. Phys. Rev. Lett. (2013)
Random Walks and Search in Time-Varying Networks. Rev. Lett. (2012)
Modeling the emergence of universality in color naming patterns. PNAS (2010)
Cultural route to the emergence of linguistic categories. PNAS (2008)
Sharp transition towards shared vocabularies in multi-agent systems. J. Stat. Mech. P06014 (2006)