Floriana Gargiulo

Irina Vorobeva, Maxime Lenormand, Germana Berlantini et al.

Science is often portrayed as a universal and self-contained system, driven solely by the internal logic of knowledge accumulation and isolated from the turbulences of the socio-political world. In this paper, we challenge this narrative by providing systematic quantitative evidence that the global scientific ecosystem is deeply shaped by geopolitical transformations. Using a large-scale dataset of scientific publications drawn from the OpenAlex database, spanning over five decades and covering virtually all countries and disciplinary areas, we track the evolution of national research profiles and show that geopolitical dynamics shape scientific agendas at multiple scales. At the global level, intrinsic scientific change is slow and cumulative, but exogenous shocks, such as Chernobyl, September 11, and COVID-19, produce rapid disruptions that synchronously reconfigure the priorities of many countries at once. At the country level, we document a broad globalization of knowledge, yet deeply heterogeneous: while Global North countries converge toward a shared international agenda, Global South countries display strong dependence on international resources alongside locally distinctive research interests. Among emerging Southern economies, scientific power is increasingly asserted through specialized and independent agendas. Finally, we observe a reorganization of global scientific influence toward a more polycentric structure, with the emergence of a Southern cluster gravitating around Brazil and Indonesia as new regional hubs.

Ilaria Bertazzi, Sylvie Huet, Guillaume Deffuant et al.

Bitcoin-otc is a peer to peer (over-the-counter) marketplace for trading with bit- coin crypto-currency. To mitigate the risks of the p2p unsupervised exchanges, the establishment of a reliable reputation systems is needed: for this reason, a web of trust is implemented on the website. The availability of all the historic of the users interaction data makes this dataset a unique playground for studying reputation dynamics through others evaluations. We analyze the structure and the dynamics of this web of trust with a multilayer network approach distin- guishing the rewarding and the punitive behaviors. We show that the rewarding and the punitive behavior have similar emergent topological properties (apart from the clustering coefficient being higher for the rewarding layer) and that the resultant reputation originates from the complex interaction of the more regular behaviors on the layers. We show which are the behaviors that correlate (i.e. the rewarding activity) or not (i.e. the punitive activity) with reputation. We show that the network activity presents bursty behaviors on both the layers and that the inequality reaches a steady value (higher for the rewarding layer) with the network evolution. Finally, we characterize the reputation trajectories and we identify prototypical behaviors associated to three classes of users: trustworthy, untrusted and controversial.