arXiv subjects

Josep Perelló

Publications and source records attributed to Josep Perelló.

17 recordsLinked to original sources

arXiv2025

Citizen science dataset on residents' urban heat perception in outdoor public spaces of climate-vulnerable neighborhoods

We present a dataset generated to investigate urban heat and thermal perception across five neighborhoods in the Barcelona metropolitan area. In collaboration with 14 non-academic partner organizations, we conducted a series of citizen science campaigns involving 439 residents as co-researchers engaged throughout all stages of the research process. Participants, residents of areas classified as highly or very highly climate-vulnerable, identified 210 public outdoor sites relevant to their daily lives. These locations were subsequently characterized using a range of spatial and environmental indicators pertinent to urban heat island effects, urban health, and climate resilience. Over the course of 48 thermal walks, participants carried portable, low-cost sensors that continuously recorded air temperature, relative humidity, and geolocation, resulting in 296,286 processed microclimatic data points. At pre-defined sites, individuals completed standardized surveys to report their Thermal Sensation Votes and Thermal Comfort Votes, yielding 5,169 self-reported entries. Sociodemographic data were also collected to further contextualize participants' responses. The resulting dataset integrates objective environmental measurements with subjective perceptions of heat, enabling point-by-point analysis of thermal experience within the urban fabric. It offers a novel, multi-dimensional resource to support research on heat, thermal inequality, and the experiential dimensions of climate vulnerability, and is intended to inform evidence-based decision-making in urban planning, public health, and climate adaptation.

physics.soc-ph↗

arXiv2025

Pedestrian mobility citizen science complements expert mapping for enhancing inclusive neighborhood placemaking

Cities are complex systems that demand integrated approaches, with increasing attention focused on the neighborhood level. This study examines the interplay between expert-based mapping and citizen science in the Primer de Maig neighborhood of Granollers, Catalonia, Spain--an area marked by poor-quality public spaces and long-standing socio-economic challenges. Seventy-two residents were organized into 19 groups to record their pedestrian mobility while engaging in protocolized playful social actions. Their GPS identified opportunity units for meaningful public space activation. Although 56% of observed actions occurred within expert-defined units, the remaining 44% took place elsewhere. Clustering analysis of geo-located action stops revealed seven distinct clusters, highlighting overlooked areas with significant social potential. These findings underscore the complementarity of top-down and bottom-up approaches, demonstrating how citizen science and community science approaches enriches urban diagnostics by integrating subjective, community-based perspectives in public space placemaking and informing inclusive, adaptive sustainable urban transformation strategies.

physics.soc-ph↗

arXiv2025

Emergence of social hierarchies in a society with two competitive groups

Agent-based models describing social interactions among individuals can help to better understand emerging macroscopic patterns in societies. One of the topics which is worth tackling is the formation of different kinds of hierarchies that emerge in social spaces such as cities. Here we propose a Bonabeau-like model by adding a second group of agents. The fundamental particularity of our model is that only a pairwise interaction between agents of the opposite group is allowed. Agent fitness can thus only change by competition among the two groups, while the total fitness in the society remains constant. The main result is that for a broad range of values of the model parameters, the fitness of the agents of each group show a decay in time except for one or very few agents which capture almost all the fitness in the society. Numerical simulations also reveal a singular shift from egalitarian to hierarchical society for each group. This behaviour depends on the control parameter $η$, playing the role of the inverse of the temperature of the system. Results are invariant with regard to the system size, contingent solely on the quantity of agents within each group. Finally, scaling laws are provided thus showing a data collapse from different model parameters and they follow a shape which can be related to the presence of a phase transition in the model.

physics.soc-ph↗

arXiv2024

Explorative pedestrian mobility GPS data from a citizen science experiment in a neighbourhood

Pedestrian GPS data are key to a better understanding of micro-mobility and micro-behaviour within a neighbourhood. These data can bring new insights into walkability and livability in the context of urban sustainability. However, pedestrian open data are scarce and often lack a context for their transformation into actionable knowledge in a neighbourhood. Citizen science and public involvement practices are powerful instruments for obtaining these data and take a community-centred placemaking approach. The study shares some 3000 GPS recordings corresponding to 19 unique trajectories made and recorded by groups of participants from three distinct communities in a relatively small neighbourhood. The groups explored the neighbourhood through a number of tasks and chose different places to stop and perform various social and festive activities. The study shares not only raw data but also processed records with specific filtering and processing to facilitate and accelerate data usage. Citizen science practices and the data-collection protocols involved are reported in order to offer a complete perspective of the research undertaken jointly with an assessment of how community-centred placemaking and operative mapping are incorporated into local urban transformation actions.

physics.soc-ph↗

arXiv2023

Discounting the distant future: What do historical bond prices imply about the long term discount rate?

We present a thorough empirical study on real interest rates by also including risk aversion through the introduction of the market price of risk. With the view of complex systems science and its multidisciplinary approach, we use the theory of bond pricing to study the long term discount rate. Century-long historical records of 3 month bonds, 10 year bonds, and inflation allow us to estimate real interest rates for the UK and the US. Real interest rates are negative about a third of the time and the real yield curves are inverted more than a third of the time, sometimes by substantial amounts. This rules out most of the standard bond pricing models, which are designed for nominal rates that are assumed to be positive. We therefore use the Ornstein-Uhlenbeck model which allows negative rates and gives a good match to inversions of the yield curve. We derive the discount function using the method of Fourier transforms and fit it to the historical data. The estimated long term discount rate is $1.7$ \% for the UK and $2.2$ \% for the US. The value of $1.4$ \% used by Stern is less than a standard deviation from our estimated long run return rate for the UK, and less than two standard deviations of the estimated value for the US. All of this once more reinforces the support for immediate and substantial spending to combat climate change.

q-fin.MF↗

arXiv2023

Home-to-school pedestrian mobility GPS data from a citizen science experiment in the Barcelona area

The analysis of pedestrian GPS datasets is fundamental to further advance on the study and the design of walkable cities. The highest resolution GPS data can characterize micro-mobility patterns and pedestrians' micro-motives in relation to a small-scale urban context. Purposed-based recurrent mobility data inside people's neighborhoods is an important source in these sorts of studies. However, micro-mobility around people's homes is generally unavailable, and if data exists, it is generally not shareable often due to privacy issues. Citizen science and its public involvement practices in scientific research are valid options to circumvent these challenges and provide meaningful datasets for walkable cities. The study presents GPS records from single-day home-to-school pedestrian mobility of 10 schools in the Barcelona Metropolitan area (Spain). The research provides pedestrian mobility from an age-homogeneous group of people. The study shares processed records with specific filtering, cleaning, and interpolation procedures that can facilitate and accelerate data usage. Citizen science practices during the whole research process are reported to offer a complete perspective of the data collected.

physics.soc-ph↗

arXiv2020

Statistical analysis and stochastic interest rate modelling for valuing the future with implications in climate change mitigation

High future discounting rates favor inaction on present expending while lower rates advise for a more immediate political action. A possible approach to this key issue in global economy is to take historical time series for nominal interest rates and inflation, and to construct then real interest rates and finally obtaining the resulting discount rate according to a specific stochastic model. Extended periods of negative real interest rates, in which inflation dominates over nominal rates, are commonly observed, occurring in many epochs and in all countries. This feature leads us to choose a well-known model in statistical physics, the Ornstein-Uhlenbeck model, as a basic dynamical tool in which real interest rates randomly fluctuate and can become negative, even if they tend to revert to a positive mean value. By covering 14 countries over hundreds of years we suggest different scenarios and include an error analysis in order to consider the impact of statistical uncertainty in our results. We find that only 4 of the countries have positive long-run discount rates while the other ten countries have negative rates. Even if one rejects the countries where hyperinflation has occurred, our results support the need to consider low discounting rates. The results provided by these fourteen countries significantly increase the priority of confronting global actions such as climate change mitigation. We finally extend the analysis by first allowing for fluctuations of the mean level in the Ornstein-Uhlenbeck model and secondly by considering modified versions of the Feller and lognormal models. In both cases, results remain basically unchanged thus demonstrating the robustness of the results presented.

q-fin.MF↗

arXiv2018

Citizen Social Lab: A digital platform for human behaviour experimentation within a citizen science framework

Cooperation is one of the behavioral traits that define human beings, however we are still trying to understand why humans cooperate. Behavioral experiments have been largely conducted to shed light into the mechanisms behind cooperation and other behavioral traits. However, most of these experiments have been conducted in laboratories with highly controlled experimental protocols but with varied limitations which limits the reproducibility and the generalization of the results obtained. In an attempt to overcome these limitations, some experimental approaches have moved human behavior experimentation from laboratories to public spaces, where behaviors occur naturally, and have opened the participation to the general public within the citizen science framework. Given the open nature of these environments, it is critical to establish the appropriate protocols to maintain the same data quality that one can obtain in the laboratories. Here, we introduce Citizen Social Lab, a software platform designed to be used in the wild using citizen science practices. The platform allows researchers to collect data in a more realistic context while maintaining the scientific rigour, and it is structured in a modular and scalable way so it can also be easily adapted for online or brick-and-mortar experimental laboratories. Following citizen science guidelines, the platform is designed to motivate a more general population into participation, but also to promote engaging and learning of the scientific research process. We also review the main results of the experiments performed using the platform up to now, and the set of games that each experiment includes. Finally, we evaluate some properties of the platform, such as the heterogeneity of the samples of the experiments and their satisfaction level, and the parameters that demonstrate the robustness of the platform and the quality of the data collected.

cs.CY↗

arXiv2017

Resource heterogeneity leads to unjust effort distribution in climate change mitigation

Fighting against climate change is a global challenge shared by nations with heterogeneous economical resources and individuals with diverse propensity for cooperation. However, we lack a clear understanding of the role of key factors such as inequality of means when diverse agents interact together towards a common goal. Here, we report the results of a collective-risk dilemma experiment in which groups of subjects were initially given either equal or unequal endowments. We found that although the collective goal was always achieved regardless of the initial capital distribution, the effort distribution was highly inequitable. Specifically, participants with fewer resources contributed significantly more to the public goods than the richer -sometimes twice as much. An unsupervised learning algorithm clustered the subjects according to their individual behavior. We found that the poorest participants congregated within the two "generous clusters" whereas the richest were mostly classified into a "greedy cluster". Our findings suggest that future policies would benefit both from reinforcing climate justice actions addressed to most vulnerable people and educating fairness instead of focusing on understanding of generic or global climate consequences, as the latter has not proven to drive equitable contributions.

physics.soc-ph↗

arXiv2016

Market Imitation and Win-Stay Lose-Shift strategies emerge as unintended patterns in market direction guesses

Decisions taken in our everyday lives are based on a wide variety of information so it is generally very difficult to assess what are the strategies that guide us. Stock market therefore provides a rich environment to study how people take decision since responding to market uncertainty needs a constant update of these strategies. For this purpose, we run a lab-in-the-field experiment where volunteers are given a controlled set of financial information -based on real data from worldwide financial indices- and they are required to guess whether the market price would go up or down in each situation. From the data collected we explore basic statistical traits, behavioural biases and emerging strategies. In particular, we detect unintended patterns of behavior through consistent actions which can be interpreted as {\it Market Imitation} and {\it Win-Stay Lose-Shift} emerging strategies, being {\it Market Imitation} the most dominant one. We also observe that these strategies are affected by external factors: the expert advice, the lack of information or an information overload reinforce the use of these intuitive strategies, while the probability to follow them significantly decreases when subjects spends more time to take a decision. The cohort analysis shows that women and children are more prone to use such strategies although their performance is not undermined. Our results are of interest for better handling clients expectations of trading companies, avoiding behavioural anomalies in financial analysts decisions and improving not only the design of markets but also the trading digital interfaces where information is set down. Strategies and behavioural biases observed can also be translated into new agent based modelling or stochastic price dynamics to better understand financial bubbles or the effects of asymmetric risk perception to price drops.

q-fin.GN↗

arXiv2015

Active and reactive behaviour in human mobility: the influence of attraction points on pedestrians

Human mobility is becoming an accessible field of study thanks to the progress and availability of tracking technologies as a common feature of smart phones. We describe an example of a scalable experiment exploiting these circumstances at a public, outdoor fair in Barcelona (Spain). Participants were tracked while wandering through an open space with activity stands attracting their attention. We develop a general modeling framework based on Langevin Dynamics, which allows us to test the influence of two distinct types of ingredients on mobility: reactive or context-dependent factors, modelled by means of a force field generated by attraction points in a given spatial configuration, and active or inherent factors, modelled from intrinsic movement patterns of the subjects. The additive and constructive framework model accounts for the observed features. Starting with the simplest model (purely random walkers) as a reference, we progressively introduce different ingredients such as persistence, memory, and perceptual landscape, aiming to untangle active and reactive contributions and quantify their respective relevance. The proposed approach may help in anticipating the spatial distribution of citizens in alternative scenarios and in improving the design of public events based on a facts-based approach.

physics.soc-ph↗

arXiv2015

Citizen Science practices for Computational Social Sciences research: The conceptualization of Pop-Up Experiments

Under the name of Citizen Science, many innovative practices in which volunteers partner with scientist to pose and answer real-world questions are quickly growing worldwide. Citizen Science can furnish ready made solutions with the active role of citizens. However, this framework is still far from being well stablished to become a standard tool for Computational Social Sciences research. We present our experience in bridging Computational Social Sciences with Citizen Science philosophy, which in our case has taken the form of what we call Pop-Up Experiments: Non-permanent, highly participatory collective experiments which blend features developed by Big Data methodologies and Behavioural Experiments protocols with ideals of Citizen Science. The main issues to take into account whenever planning experiments of this type are classified and discused grouped in three categories: public engagement, light infrastructure and knowledge return to citizens. We explain the solutions implemented providing practical examples grounded in our own experience in urban contexts (Barcelona, Spain). We hope that this work serves as guideline to groups willing to adopt and expand such \emph{in-vivo} practices and opens the debate about the possibilities (but also the limitations) that the Citizen Science framework can offer to study social phenomena.

cs.CY↗

arXiv2013

Uncertain growth and the value of the future

For environmental problems such as global warming future costs must be balanced against present costs. This is traditionally done using an exponential function with a constant discount rate, which reduces the present value of future costs. The result is highly sensitive to the choice of discount rate and has generated a major controversy as to the urgency for immediate action. We study analytically several standard interest rate models from finance and compare their properties to empirical data. From historical time series for nominal interest rates and inflation covering 14 countries over hundreds of years, we find that extended periods of negative real interest rates are common, occurring in many epochs in all countries. This leads us to choose the Ornstein-Uhlenbeck model, in which real short run interest rates fluctuate stochastically and can become negative, even if they revert to a positive mean value. We solve the model in closed form and prove that the long-run discount rate is always less than the mean; indeed it can be zero or even negative, despite the fact that the mean short term interest rate is positive. We fit the parameters of the model to the data, and find that nine of the countries have positive long run discount rates while five have negative long-run discount rates. Even if one rejects the countries where hyperinflation has occurred, our results support the low discounting rate used in the Stern report over higher rates advocated by others.

q-fin.ST↗

arXiv2013

Volatility polarization of non-specialized investors' heterogeneous activity

Financial markets provide an ideal frame for studying decision making in crowded environments. Both the amount and accuracy of the data allows to apply tools and concepts coming from physics that studies collective and emergent phenomena or self-organised and highly heterogeneous systems. We analyse the activity of 29,930 non-expert individuals that represent a small portion of the whole market trading volume. The very heterogeneous activity of individuals obeys a Zipf's law, while synchronization network properties unveil a community structure. We thus correlate individual activity with the most eminent macroscopic signal in financial markets, that is volatility, and quantify how individuals are clearly polarized by volatility. The assortativity by attributes of our synchronization networks also indicates that individuals look at the volatility rather than imitate directly each other thus providing an interesting interpretation of herding phenomena in human activity. The results can also improve agent-based models since they provide direct estimation of the agent's parameters.

q-fin.ST↗

arXiv2012

First-passage and escape problems in the Feller process

The Feller process is an one-dimensional diffusion process with linear drift and state-dependent diffusion coefficient vanishing at the origin. The process is positive definite and it is this property along with its linear character that have made Feller process a convenient candidate for the modeling of a number of phenomena ranging from single neuron firing to volatility of financial assets. While general properties of the process are well known since long, less known are properties related to level crossing such as the first-passage and the escape problems. In this work we thoroughly address these questions.

math-ph↗

arXiv2012

Maximum likelihood approach for several stochastic volatility models

Volatility measures the amplitude of price fluctuations. Despite it is one of the most important quantities in finance, volatility is not directly observable. Here we apply a maximum likelihood method which assumes that price and volatility follow a two-dimensional diffusion process where volatility is the stochastic diffusion coefficient of the log-price dynamics. We apply this method to the simplest versions of the expOU, the OU and the Heston stochastic volatility models and we study their performance in terms of the log-price probability, the volatility probability, and its Mean First-Passage Time. The approach has some predictive power on the future returns amplitude by only knowing current volatility. The assumed models do not consider long-range volatility auto-correlation and the asymmetric return-volatility cross-correlation but the method still arises very naturally these two important stylized facts. We apply the method to different market indexes and with a good performance in all cases.

q-fin.CP↗

arXiv2011

Scaling properties and universality of first-passage time probabilities in financial markets

Financial markets provide an ideal frame for the study of crossing or first-passage time events of non-Gaussian correlated dynamics mainly because large data sets are available. Tick-by-tick data of six futures markets are herein considered resulting in fat tailed first-passage time probabilities. The scaling of the return with the standard deviation collapses the probabilities of all markets examined, and also for different time horizons, into single curves, suggesting that first-passage statistics is market independent (at least for high-frequency data). On the other hand, a very closely related quantity, the survival probability, shows, away from the center and tails of the distribution, a hyperbolic $t^{-1/2}$ decay typical of a Markovian dynamics albeit the existence of memory in markets. Modifications of the Weibull and Student distributions are good candidates for the phenomenological description of first-passage time properties under certain regimes. The scaling strategies shown may be useful for risk control and algorithmic trading.

q-fin.ST↗