Professor of Complex Systems

Department of Biomedical Engineering and Computational Science (BECS)

                  Aalto University, Espoo, Finland                               


  • The special issue Statistical Mechanics and Social Sciences, edited by Michael Macy, Sidney Redner and myself, has just been published in the Journal of Statistical Physics. You can find the contents here (Volume I, Volume II). Read our editorial for a brief overview.
  • My historical-philosophical introduction to the concept of social atom, first class of my course Mathematical modeling of social dynamics, can be seen here
  • My keynote talk Community detection in networks opened the European Conference on Complex Systems 2012 (ECCS'12), Brussels (September the 3rd, 2012)   
  • I have been named Distinguished Referee for Europhysics Letters for the second time in a row (2010, 2011).
  • On November the 16th, 2011, I have given my Installation Lecture at Aalto University, a short pedagogical presentation of the history and principles of sociophysics. The video of the lecture can be seen here
  • I am the winner of the Young Scientist Award for Socio- and Econophysics 2011. The award ceremony was held at the annual meeting of the German Physical Society in Dresden, on March 14th, 2011 (photos: 1, 2, 3, 4). Following the reception of the award, two articles on myself and my work appeared in the newspaper Italia Oggi and in the popular magazine L'Espresso.

Recent papers

  • In the commentary The case for caution in predicting scientists' future impact Physics Today 66 (4), 8-9, 2013], we warn against the indiscriminate use of quantitative indicators of scientific impact, particularly the h-index, to evaluate academic careers, especially for young scientists.
  • The paper Universality in voting behavior: an empirical analysis (Scientific Reports 3, 1049, 2013) shows that proportional elections with open lists lead to the same pattern for the distribution of performance of candidates across countries and years. Deviations from the general pattern are associated to specific differences in the election rules.
  • In the paper World citation and collaboration networks: uncovering the role of geography in science (Scientific Reports 2, 902, 2012) we study the streams of citations and collaborations between different geographic locations, finding that they obey simple gravity laws.
  • Take a look at our recent paper on the physics of elections: Physics peeks into the ballot box, Physics Today 65 (10), 74-75, 2012
  • In the paper Characterizing and modeling citation dynamics (PLoS One 6, e24926, 2011) we find that citation distributions of networks of papers of the Americal Physical Society are described by shifted power laws and that citation dynamics is characterized by bursts in the early life of papers. Both features can be accounted for by a modified version of linear preferential attachment, where the paper attractiveness is heterogeneously distributed and decays with time.
  • How do Nobel Prize Laureates accrue their scientific reputation? In the paper How citation boosts promote scientific paradigm shifts and Nobel Prizes (PLoS One 6, e18975, 2011) we show that groundbreaking discoveries make previous publications of the author visible and cited, even in different topics. This "authority effect" is measurable and can be used to distinguish outstanding scholars from normal ones. See the feature by Philip Ball on Nature News!
  • In the paper Finding statistically significant communities in networks (PLoS One 6, e18961, 2011) we present OSLOM, the first multi-purpose method to find communities in graphs, accounting for edge directions, edge weights, overlapping communities, hierarchies and community dynamics.
  • What are the principles behind the dynamics of online popularity? In the paper Characterizing and modeling the dynamics of online popularity (Phys. Rev. Lett. 105, 158701, 2010) we show that popularity in online media does not change smoothly, but it experiences wild fluctuations, following power law distributions, due to exogenous factors.
  • What do communities in real networks look like? In the paper Characterizing the community structure of complex networks (PLoS One 5, e11976, 2010) we have made a systematic analysis of various networked datasets, finding that communities can be categorized in classes according to their statistical properties and that each class comprises networks of the same (or similar) origin (communication, information, biological, social and technological networks).
  • What is the best algorithm to find communities in networks? In the paper Community detection algorithms: a comparative analysis (Phys. Rev. E 80, 056117, 2009) we have tested the performances of several graph clustering methods on the benchmark graphs we have recently introduced. As a result, the Infomap method by Rosvall and Bergstrom appears to be the most reliable and should be adopted as a first approach, especially when one has no specific information on the network at study. 
  • The paper Community detection in graphs (Phys. Rep. 486, 75-174, 2010) is the first comprehensive review article on the problem of graph clustering, which consists in identifying clusters of vertices with a high internal density of edges, whereas the density of edges between clusters is comparatively low.