Sofia Morena del Pozo

arXiv2022

News-sharing on Twitter reveals emergent fragmentation of media agenda and persistent polarization

News sharing on social networks reveals how information disseminates among users. This process, constrained by user preferences and social ties, plays a key role in the formation of public opinion. In this work we study news sharing of main Argentinian media outlets in Twitter, using bipartite news-user networks, in order to understand if the emergence of affinity groups is driven by the underlying political polarization. We compare the results between an electoral and non-electoral year and between a set of politically active users and a control group. We found that users' behavior produces well differentiated communities of news articles identified by a unique distribution of media outlets in all analyzed datasets. In particular, these communities split into two groups which reflect the dominant ideological polarization in Argentina. We also found that users form two well differentiated groups identified by their preferences in media outlets consumption. These two groups of media outlets display a bias towards the two main political parties that rule the political life in Argentina. These results reveal consistently that ideological polarization is the main driving force shaping the Argentinian news sharing in Twitter.

physics.soc-ph↗

arXiv2020

Unconsciousness reconfigures modular brain network dynamics

The dynamic core hypothesis posits that consciousness is correlated with simultaneously integrated and differentiated assemblies of transiently synchronized brain regions. We represented time-dependent functional interactions using dynamic brain networks, and assessed the integrityof the dynamic core by means of the flexibility and largest multilayer module of these networks. As a first step, we constrained parameter selection using a newly developed benchmark for module detection in heterogeneous temporal networks. Next, we applied a multilayer modularity maximization algorithm to dynamic brain networks computed from functional magnetic resonance imaging (fMRI) data acquired during deep sleep and under propofol anesthesia. We found that unconsciousness reconfigured network flexibility and reduced the size of the largest spatiotemporal module, which we identified with the dynamic core. Our results present a first characterization of modular brain network dynamics during states of unconsciousness measured with fMRI, adding support to the dynamic core hypothesis of human consciousness.

q-bio.NC↗