Structure and dynamics of Urban Complex Systems

 

Urban areas are socio-economic systems that take up space in a particular geography. They are built upon tightly knitted layers of personal interactions and infrastructural networks (communication, transportation, services) offering, in turn, outstanding opportunities for living and working. However, their impact on the surrounding environment is extensive leaving behind a significant footprint –not only ecological, but also in terms of public health, social discrimination, etc. This view of cities creates interdisciplinary opportunities and challenges, bringing together data science, GIS, multiplex complex networks and social science, with consequences for policy decision makers, or landscape and urban planners. 

 

With the increasing popularity of open data technologies and portals, a vast amount of information about these layers is now available to us. This information ranges from structural and dynamical information about the different cities’ infrastructures (collected by sensors deployed in a city) to social information about urban dwellers. 

Within this topic, the group’s activities revolve around the following lines:

 

- Sidewalk networks and pedestrian dynamics. Among all transportation modes, pedestrian mobility (and its associated infrastructure, sidewalks) has been the most neglected by large. This is in part due to a general lack of open data on this urban resource, but also, probably, because of the pressing challenges that stem from car-oriented cities (congestion, pollution). Following existing research [1,2,5], this proposal aims at a better understanding of pedestrian space both as a mobility and a social interaction asset.

 

- Dynamics of transportation systems. Data-driven research, exploiting complexity theory (complex networks, percolation, self-organized criticality, agent-based modeling), helps in understanding the internal city dynamics and achieving sustainability from a transportation perspective, improving efficiency and performance [3,4]. This includes multimodal transportation systems: surface (private and public) connected to underground (public) transport, represented as multiplex complex networks.

 

- City resilience comprises the assessment and understanding of the robustness [1,6], “stress limits”, and recovery capacity of the networks of infrastructures. These measures are strongly related to crisis response in case of emergencies (traffic re-routing, accident assistance).

 

 

[1] D Rhoads, A Solé-Ribalta, MC González, J Borge-Holthoefer. A sustainable strategy for Open Streets in (post) pandemic cities. Communications Physics 4 (1), 1-12 (2021) 

[2] D Rhoads, C Rames, A Solé-Ribalta, M C. González, M Szell, J Borge-Holthoefer. Sidewalk networks: Review and outlook. Computers, Environment and Urban Systems 106, 102031 (2023)

[3] A Solé-Ribalta, S Gómez and A Arenas. Congestion induced by the structure of multiplex networks. Physical Review Letters 116(10), 108701 (2016) 

[4] A Lampo, J Borge-Holthoefer, S Gómez, A Solé-Ribalta. Multiple abrupt phase transitions in urban transport congestion. Physical Review Research 3 (1), 013267 (2021) 

[5] D Rhoads, A Solé-Ribalta, J Borge-Holthoefer. The inclusive 15-minute city: Walkability analysis with sidewalk networks. Computers, Environment and Urban Systems 100, 101936 (2023) 

[6] S Abbar, T Zanouda, J Borge-Holthoefer. Structural robustness and service reachability in urban settings. Data Mining and Knowledge Discovery 32 (3), 830-847 (2018)

The aim of this program is to address the question of ICT-mediated social phenomena emerging over multiple scales, ranging from the interactions of individuals to the emergence of self-organized global movements. The group displays its activity on the following topics:

 

- Emerging patterns in online communication systems [1,2].

- User-information interplay: information ecosystems [1,2].

- Temporal and geographical patterns of information diffusion [3].

- Modeling, tracking, and forecasting dynamic groups in social media [1,2,3].

- Social simulation, cultural, opinion, and normative dynamics [4].

 

On the other hand, the group is involved in the ERC Starting Grant project “Social Networks of the Past. Mapping Hispanic and Lusophone Literary Modernity, 1898-1959”, led by Dr. Diana Roig Sanz. For this project, CoSIN3 focuses as well on these topics:

 

- Extraction, analysis, and modelling of cultural/artistic/literary networks from records available in online repositories (e.g., the International Committee on Intellectual Cooperation). Special emphasis will on the use of a multilayer/multiplex approach [5,6], as well as on the role of gender-based differences [7,8].

 

[1] MJ Palazzi, A Solé-Ribalta, V Calleja-Solanas, S Meloni, CA Plata, S Suweis, J Borge-Holthoefer. An ecological approach to structural flexibility in online communication systems. Nature Communications 12 (1), 1-11 (2021).

[2] J Borge-Holthoefer, RA Baños, C Gracia-Lázaro and Y Moreno. The nested assembly of collective attention in online social systems. Scientific Reports (2017)

[3] J Borge-Holthoefer, N Perra, B Gonçalves, S González-Bailón, A Arenas, Y Moreno and A Vespignani. The dynamic of information-driven coordination phenomena: a transfer entropy analysis. Science Advances 2(4), e1501158 (2016)

[4] P Piedrahita, J Borge-Holthoefer, Y Moreno, S González-Bailón. The contagion effects of repeated activation in social networks. Social Networks 54, 326-335 (2018)

[5] M De Domenico, A Solé-Ribalta, E Cozzo, et al. “Mathematical formulation of multilayer networks”. Physical Review X 3 (4), 041022 (2013)

[6] M Grandjean. “A Conceptual Framework for the Analysis of Multilayer Networks in the Humanities.” Digital Humanities (2020)

[7] M Schich, C Song, YY Ahn, A Mirsky, M Martino, AL Barabási, D Helbing. A network framework of cultural history. Science 345 (6196), 558-562 (2014)

[8] D Roig-Sanz, J Subirana (Eds.). Cultural Organizations, Networks and Mediators in Contemporary Ibero-America. Taylor & Francis (2020)

Often unnoticed, one of the main contributions of Complex Systems to the scientific community comes under the form of new descriptors, innovative algorithms or modelling developments: take for instance community detection techniques, which are nowadays standard tools in many areas. Along this line, a Complex Systems research group permanently works in the creation (or adaptation) of methods and software that yield better, deeper insight in the understanding of the problems it deals with. Of particular interest, the group has focused on hybrid network structures (e.g., those that combine modularity with nestedness [1-3]).

 

Of course, such attention is related not only to the structural side, but also to the dynamical one: for example, the implications of hybrid network structures patterns in the performance of ecological and sociotechnical systems [4-6], or the development of co-evolutionary models that improve our understanding of biological and social systems [7].

 

[1] A Solé-Ribalta, CJ Tessone, MS Mariani, J Borge-Holthoefer. Revealing in-block nestedness: detection and benchmarking. Physical Review E 97 (6), 062302 (2018)

[2] MJ Palazzi, J Borge-Holthoefer, CJ Tessone, A Solé-Ribalta. Macro-and mesoscale pattern interdependencies in complex networks. Journal of the Royal Society Interface 16 (159), 20190553 (2019)

[3] MS Mariani, MJ Palazzi, A Solé-Ribalta, J Borge-Holthoefer, CJ Tessone. Absence of a resolution limit in in-block nestedness. Communications in Nonlinear Science and Numerical Simulation 94 (2021)

[4] MJ Palazzi, A Solé-Ribalta, V Calleja-Solanas, S Meloni, CA Plata, S Suweis, J Borge-Holthoefer. An ecological approach to structural flexibility in online communication systems. Nature Communications 12 (1), 1-11 (2021)

[5] MJ Palazzi, J Cabot, JLC Izquierdo, A Solé-Ribalta, J Borge-Holthoefer. Online division of labour: emergent structures in Open Source Software. Scientific Reports 9, 13890 (2019)

[6] A Lampo, MJ Palazzi, J Borge-Holthoefer, A Solé-Ribalta. Hybrid structural arrangements mediate stability and feasibility in mutualistic networks. arXiv:2105.09191 (pre-print, 2021)

[7] M Perc, A Szolnoki. Coevolutionary games - A mini review. Biosystems, 99(2), 109–125 (2010)