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[eng] Complex systems show the capacity to aggregate information and to display coordinated activity. In the case of social systems the interaction of different individuals leads to the emergence of norms, trends in political positions, opinions, cultural traits, and even scientific progress. Examples of collective behavior can be observed in activities like the Wikipedia and Linux, where individuals aggregate their knowledge for the benefit of the community, and citizen science, where the potential of collectives to solve complex problems is exploited. Here, we conducted an online experiment to investigate the performance of a collective when solving a guessing problem in which each actor is endowed with partial information and placed as the nodes of an interaction network. We measure the performance of the collective in terms of the temporal evolution of the accuracy, finding no statistical difference in the performance for two classes of networks, regular lattices and random networks. We also determine that a Bayesian description captures the behavior pattern the individuals follow in aggregating information from neighbors to make decisions. In comparison with other simple decision models, the strategy followed by the players reveals a suboptimal performance of the collective. Our contribution provides the basis for the micro-macro connection between individual based descriptions and collective phenomena.

Complex systems show the capacity to aggregate information and to display coordinated activity. In the case of social systems the interaction of different individuals leads to the emergence of norms, trends in political positions, opinions, cultural traits, and even scientific progress. Examples of collective behavior can be observed in activities like the Wikipedia and Linux, where individuals aggregate their knowledge for the benefit of the community, and citizen science, where the potential of collectives to solve complex problems is exploited. Here, we conducted an online experiment to investigate the performance of a collective when solving a guessing problem in which each actor is endowed with partial information and placed as the nodes of an interaction network. We measure the performance of the collective in terms of the temporal evolution of the accuracy, finding no statistical difference in the performance for two classes of networks, regular lattices and random networks. We also determine that a Bayesian description captures the behavior pattern the individuals follow in aggregating information from neighbors to make decisions. In comparison with other simple decision models, the strategy followed by the players reveals a suboptimal performance of the collective. Our contribution provides the basis for the micro-macro connection between individual based descriptions and collective phenomena. ; The authors acknowledge support from Spanish Ministry of Economy and Competitiveness (MINECO) and FEDER (EU) through the projects MODASS (FIS2011-24785) (VME) and INTENSE@COSYP (FIS2012-30634). TP acknowledges support from the program Juan de la Cierva of MINECO. ; Peer Reviewed

ArXiv Number: 1102.3118.- PACS numbers: 89.75.-k, 05.10.-a, 87.23.G ; We introduce a general methodology of update rules accounting for arbitrary interevent time distributions in simulations of interacting agents. In particular we consider update rules that depend on the state of the agent, so that the update becomes part of the dynamical model. As an illustration we consider the voter model in fully-connected, random and scale free networks with an update probability inversely proportional to the persistence, that is, the time since the last event. We find that in the thermodynamic limit, at variance with standard updates, the system orders slowly. The approach to the absorbing state is characterized by a power law decay of the density of interfaces, observing that the mean time to reach the absorbing state might be not well defined. ; We acknowledge nancial support from MICINN(Spain) through project FISICOS (FIS2007- 60327). J.F.-G. aknowledges a predoctoral fellowship form the Government of the Balearic Islands. ; Peer reviewed

The original publication is available at Springer website: http://www.springer.com/computer/mathematics/book/978-4-431-73150-4. ; In the general context of dynamics of social consensus, we study an agent based model for the competition between two socially equivalent languages, addressing the role of bilingualism and social structure. In a regular network, we study the formation of linguistic domains and their interaction across the boundaries. We analyse also a small world social structure, in order to capture the effect of long range social interactions. In both cases, a final scenario of dominance of one language and extinction of the other is obtained, but with smaller times for extinction in the latter case. In addition, we compare our results to our previous work on the agent based version of Abrams-Strogatz model. ; We acknowledge financial support from the MEC (Spain) through project CONOCE2 (FIS2004-00953). X. C. also acknowledges financial support from a Ph.D. fellowship of the Govern de les Illes Balears (Spain). L. L-P. also acknowledges financial support from the Autonomous Government of Galicia (PGIDIT05PXIC20401PN), and the MEC (Spain) and the ERDF (HUM2004-00940). ; http://dx.doi.org/10.1007/978-4-431-73167-2

Studies of cultural differentiation have shown that social mechanisms that normally lead to cultural convergence—homophily and influence—can also explain how distinct cultural groups can form. However, this emergent cultural diversity has proven to be unstable in the face of cultural drift—small errors or innovations that allow cultures to change from within. The authors develop a model of cultural differentiation that combines the traditional mechanisms of homophily and influence with a third mechanism of network homophily, in which network structure co-evolves with cultural interaction. Results show that in certain regions of the parameter space, these co-evolutionary dynamics can lead to patterns of cultural diversity that are stable in the presence of cultural drift. The authors address the implications of these findings for understanding the stability of cultural diversity in the face of increasing technological trends toward globalization.

J. F.-G. receives economic support from the Conselleria d'Educació, Cultura i Universitats of the Government of the Balearic Islands and the ESF. J. J. R. acknowledges funding from the Ramón y Cajal program of the Spanish Ministry of Economy (MINECO). Partial support was received from MINECO and FEDER through projects FIS2011-24785 and FIS2012-30634 and from the EU Commission through the FP7 projects EUNOIA and LASAGNE. ; Peer reviewed

The voter model has been studied extensively as a paradigmatic opinion dynamics model. However, its ability to model real opinion dynamics has not been addressed. We introduce a noisy voter model (accounting for social influence) with recurrent mobility of agents (as a proxy for social context), where the spatial and population diversity are taken as inputs to the model. We show that the dynamics can be described as a noisy diffusive process that contains the proper anisotropic coupling topology given by population and mobility heterogeneity. The model captures statistical features of U.S. presidential elections as the stationary vote-share fluctuations across counties and the long-range spatial correlations that decay logarithmically with the distance. Furthermore, it recovers the behavior of these properties when the geographical space is coarse grained at different scales - from the county level through congressional districts, and up to states. Finally, we analyze the role of the mobility range and the randomness in decision making, which are consistent with the empirical observations. © 2014 American Physical Society. ; J. F.-G. receives economic support from the Conselleria d'Educació, Cultura i Universitats of the Government of the Balearic Islands and the ESF. J. J. R. acknowledges funding from the Ramón y Cajal program of the Spanish Ministry of Economy (MINECO). Partial support was received from MINECO and FEDER through projects FIS2011-24785 and FIS2012-30634 and from the EU Commission through the FP7 projects EUNOIA and LASAGNE. ; Peer Reviewed

Trabajo presentado en la Conference on Complex Systems (CCS), celenbrada en Lyon del 25 al 29 de octubre de 2021. ; Human activities and natural resources are coupled through biological, economical, political and social aspects. In particular, fishing is a complex activity due to the interaction of multiple factors. For example, there is an interplay between the specific interests of extracting industries and those of nations, having the right to regulate fishing within their Exclusive Economic Zones (EEZs). The problem of sustainable fishing becomes harder at the Areas Beyond National Jurisdiction (high seas), where the fishing stocks are shared resources and the regulation is weaker. We analyse one year of fishing vessels' trajectories, obtained from the Automatic Identification System (AIS), to understand how fishing is distributed at the high seas. We find an accumulation of fishing effort at the external borders of the most productive EEZs, hindering the sustainable fishing within those waters, such that 47% of the fishing effort in the high seas concentrates in a 200 km strip adjacent to the EEZ borders. To quantify this observation, we obtain 14 marine provinces from the trajectories of the vessels and link these provinces to the ports that give support to the vessels fishing on them. This leads to a global network where typically the ports are specialized on one or two provinces, and those located in low and middle-income countries have a key role, becoming potential candidates to receive rewards for control and catch verification tasks.

The Spanish government declared the lockdown on March 14th, 2020 to tackle the fast-spreading of COVID-19. As a consequence the Balearic Islands remained almost fully isolated due to the closing of airports and ports, These isolation measures and the home-based confinement have led to a low incidence of COVID-19 in this region. We propose a compartmental model for the spread of COVID-19 including five compartments (Susceptible, Latent, Infected, Diseased, and Recovered), and the mobility between municipalities. The model parameters are calibrated with the temporal series of confirmed cases provided by the Spanish Ministry of Health. After calibration, the proposed model captures the trend of the official confirmed cases before and after the lockdown. We show that the estimated number of cases depends strongly on the initial dates of the local outbreak onset and the number of imported cases before the lockdown. Our estimations indicate that the population has not reached the level of herd immunization necessary to prevent future outbreaks. While the low incidence, in comparison to mainland Spain, has prevented the saturation of the health system, this low incidence translates into low immunization rates, therefore facilitating the propagation of new outbreaks that could lead to secondary waves of COVID-19 in the region. These findings warn about scenarios regarding after-lockdown-policies and the risk of second outbreaks, emphasize the need for widespread testing, and could potentially be extrapolated to other insular and continental regions. ; V.M.E. and J.F.G. acknowledge funding from the Ministry of Science and Innovation (Spain) and FEDER through project SPASIMM [FIS2016-80067-P (AEI/FEDER, UE)]. JFG acknowledges funding through the postdoc program of the University of the Balearic Islands. ; No

The Spanish government declared the lockdown on March 14th, 2020 to tackle the fast-spreading of COVID-19. As a consequence, the Balearic Islands remained almost fully isolated due to the closing of airports and ports, these isolation measures and the home-based confinement have led to a low prevalence of COVID-19 in this region. We propose a compartmental model for the spread of COVID-19 including five compartments (Susceptible, Exposed, Presymptomatic Infective, Diseased, and Recovered), and the mobility between municipalities. The model parameters are calibrated with the temporal series of confirmed cases provided by the Spanish Ministry of Health. After calibration, the proposed model captures the trend of the official confirmed cases before and after the lockdown. We show that the estimated number of cases depends strongly on the initial dates of the local outbreak onset and the number of imported cases before the lockdown. Our estimations indicate that the population has not reached the level of herd immunization necessary to prevent future outbreaks. While the low prevalence, in comparison to mainland Spain, has prevented the saturation of the health system, this low prevalence translates into low immunization rates, therefore facilitating the propagation of new outbreaks that could lead to secondary waves of COVID-19 in the region. These findings warn about scenarios regarding after-lockdown-policies and the risk of second outbreaks, emphasize the need for widespread testing, and could potentially be extrapolated to other insular and continental regions. ; VE and JF-G acknowledge funding from the Ministry of Science and Innovation (Spain) and FEDER through project SPASIMM [FIS2016-80067-P (AEI/FEDER, UE)]. JF-G acknowledges funding from the Vicerrectorado de Investigación e Internacionalización of the University of the Balearic Islands and Campus de Excelencia Internacional CEI15-09 (Ministerio de Educación, Cultura y Deporte, Spain) through its talent attraction program. ; Peer reviewed