Julián Vicens | Searcharxiv

arXiv2026

A citizen science behavioural dataset of an urban collective-risk dilemma on air pollution mitigation under resource inequality

This article describes a behavioural dataset from a collective-risk dilemma public experiment carried out in Barcelona, Spain, within the citizen science \textit{xAire} air quality project. Participants played a ten-round game in groups of six, each deciding every round how many monetary units to contribute from a private endowment toward a shared target; groups that fell short forfeited all remaining capital. Three endowment treatments held the group total fixed: an equal condition and two unequal conditions in which low-endowment participants formed either the minority or the majority of the group. Data were collected at two public outdoor venues using a tablet-based interface under lab-in-the-field protocols. Participants were recruited on-site from a demographically heterogeneous pool of individuals passing through the venues, mostly local residents. The dataset comprises 462 participants across 77 six-player games, 4\,620 contribution decisions in total. Each participant record links the full ten-round contribution trajectory to initial endowment, wealth treatment, venue, district of residence and its measured nitrogen-dioxide concentration, and socio-demographic and attitudinal survey items covering gender, age, education, economic and working status, air-quality perception, fairness norms, environmental-justice beliefs, residential mobility, and community participation. The release provides raw and cleaned participant tables, a variable codebook, the survey instrument, the district-pollution linkage, and the preprocessing code.

physics.soc-ph↗

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↗