Multilayer Network Science

From a complexity perspective on governance, multilateral diplomacy is based on interactions between people, ideas, norms, policies and institutions. This article uses a computer-assisted methodology to better understand governance systems as a network of norms. All World Health Assembly (WHA) resolutions that were available from 1948 to 2022 were collected from the WHO Institutional Repository for Information Sharing (IRIS) database. Regular expressions were used to identify how resolutions cite other resolutions and the resulting relationships were analysed as a normative network. The findings show that WHA resolutions constitute a complex network of interconnected global health issues. This network is characterised by several community patterns. While chain-like patterns are associated with specific diseases programmes, radial patterns are characteristic of highly important procedural decisions that member states reaffirm in similar situations. Finally, densely connected communities correspond to contested topics and emergencies. While these emergeng patterns suggest the relevance of using network analysis to understand global health norms in international organisations, we reflect on how this computational approach can be extended to provide new understandings of how multilateral governance systems work, and to address some important contemporary questions about the effects of regime complexity on global health diplomacy.

show abstract

“…These additional documents may be mapped as new nodes and layers in what would become a multilayered network approach of governance. 41 42 …”

Section: Discussionmentioning

confidence: 99%

Emergent patterns in global health diplomacy: a network analysis of the resolutions adopted by the World Health Assembly from 1948 to 2022

et al. 2023

View full text Add to dashboard Cite

show abstract

“…On these bases, we envision promising extensions of the mathematical framework presented here due to its flexibility, such as including more complex resetting statistics [51], modifying the dynamical rules underlying the walker moves, and considering more realistic network topologies, such as multilayer [71] and higher-order networks [72]. We hope that our results become a stepping stone on the path toward improving network exploration, navigability and discovery, in particular, and toward disentangling the intricate interplay between memory and topology in complex systems, in general.…”

Section: Discussionmentioning

confidence: 99%

Efficient network exploration by means of resetting self-avoiding random walkers

Colombani,

Bertagnolli,

Artime

2023

J. Phys. Complex.

View full text Add to dashboard Cite

The self-avoiding random walk (SARW) is a stochastic process whose state variable avoids returning to previously visited states. This non-Markovian feature has turned SARWs a powerful tool for modeling a plethora of relevant aspects in network science, such as network navigability, robustness and resilience. We analytically characterize self-avoiding random walkers that evolve on complex networks and whose memory suffers stochastic resetting, that is, at each step, with a certain probability, they forget their previous trajectory and start free diffusion anew. Several out-of-equilibrium properties are addressed, such as the time-dependent position of the walker, the time-dependent degree distribution of the non-visited network and the first-passage time distribution, and its moments, to target nodes. We examine these metrics for different resetting parameters and network topologies, both synthetic and empirical, and find a good agreement with simulations in all cases. We also explore the role of resetting on network exploration and report a non-monotonic behavior of the cover time: frequent memory resets induce a global minimum in the cover time, significantly outperforming the well-known case of the pure random walk, while reset events that are too spaced apart become detrimental for the network discovery. Our results provide new insights into the profound interplay between topology and dynamics in complex networks, and shed light on the fundamental properties of SARWs in nontrivial environments.

show abstract

“…Examples of complex systems include living organisms, an organization, an ecosystem, the economy, society as a whole, and the biosphere (Mitchell, 2009; Ruhl, 1996). Many complex systems can be described as co‐evolving multi‐layered networks (Artime et al, 2022; Kivelä et al, 2014; Thurner et al, 2018). Their overall behaviour crucially depends on structural details and usually cannot be described by reductionist approaches (Parisi, 1999).…”

Section: Understanding Systemic Crises Under a Complexity Lensmentioning

confidence: 99%

Understanding and governing global systemic crises in the 21st century: A complexity perspective

et al. 2023

View full text Add to dashboard Cite

Contemporary globalization has fostered human development but growing interconnectivity between societies has increased systemic risks (Goldin & Mariathasan, 2014;Goldin & Vogel, 2010). Systemic risks are risks associated with large-scale failures or changes of a system (Helbing, 2013). Disruptions originating in one country can quickly spread beyond national borders and affect large parts of the human population. Addressing such threats is considered a global public good, i.e., goods with benefits that extend to all countries (Kaul et al., 1999). In the study of risks with large-scale impacts, research has often focused on wars, natural disasters, and existential risks (Ord, 2020). However, crises affecting human societies are also related to economic and social issues, or the cooccurrence of social and ecological phenomena (Folke et al., 2021). In the early 21st century, the world has experienced several systemic events with global repercussions, including jihadist terrorism and the war on terror (2001), the global financial and economic crisis ( 2008), the COVID-19 pandemic (2020), and the current broader impact of the Russian aggression against Ukraine on energy, food, and security (2022).These events have provided an empirical basis to study systemic crises. This article aims at providing a broader understanding of the nature, causes, mechanisms, and impact of global systemic crises and their implications for global policymaking and governance. Such understanding is essential for the provision of global public goods to prevent, react to, and recover from shocks. The article

show abstract

Multilayer Network Science

Cited by 31 publications

References 320 publications

Emergent patterns in global health diplomacy: a network analysis of the resolutions adopted by the World Health Assembly from 1948 to 2022

Emergent patterns in global health diplomacy: a network analysis of the resolutions adopted by the World Health Assembly from 1948 to 2022

Efficient network exploration by means of resetting self-avoiding random walkers

Understanding and governing global systemic crises in the 21st century: A complexity perspective

Contact Info

Product

Resources

About