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

TL;DR

This paper introduces Pop-Up Experiments, a participatory Citizen Science approach blending Big Data and Behavioral Experiments to study social phenomena, with practical guidelines based on urban case studies.

Contribution

It conceptualizes and discusses Pop-Up Experiments as a novel, non-permanent Citizen Science methodology for Computational Social Sciences research.

Findings

Practical solutions for public engagement and infrastructure

Case studies in Barcelona demonstrate feasibility

Guidelines for implementing Pop-Up Experiments

Abstract

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.