Abstract

Under the name of Citizen Science, many innovative practices in which volunteers partner up with scientists to pose and answer real-world questions are growing rapidly worldwide. Citizen Science can furnish ready-made solutions with citizens playing an active role. However, this framework is still far from being well established as a standard tool for computational social science research. Here, we present our experience in bridging gap between computational social science and the philosophy underlying Citizen Science, which in our case has taken the form of what we call ``pop-up experiments. These are non-permanent, highly participatory collective experiments which blend features developed by big data methodologies and behavioural experimental protocols with the ideals of Citizen Science. The main issues to take into account whenever planning experiments of this type are classified, discussed and grouped into three categories: infrastructure, public engagement, and the knowledge return for citizens. We explain the solutions we have implemented, providing practical examples grounded in our own experience in an urban context (Barcelona, Spain). Our aim here is that this work will serve as a guideline for groups willing to adopt and expand such \emph{in-vivo} practices and we hope it opens up the debate regarding the possibilities (and also the limitations) that the Citizen Science framework can offer the study of social phenomena.

Highlights

  • The relationship between knowledge and society has always been an important aspect to consider when one tries to understand how science advances and how research is performed [1, 2]

  • The approach we present aims to explore the potential of blending interesting features recently developed by big data methodologies with the ambitious and democratic ideals of Citizen Science (CS)

  • To understand the context in which the pop-up experiments" (PUEs) we propose can be placed better, Figure 2 compares the different approaches considered using a radar chart that qualitatively measures, with three degrees of intensity, six different aspects that characterize each type of experiment

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Summary

Introduction

The relationship between knowledge and society has always been an important aspect to consider when one tries to understand how science advances and how research is performed [1, 2]. The general public has, mostly been left out of this methodology and creation processes [3, 4]. Citizens are generally considered as passive subjects to whom only finished results are presented in the form of simplified statements; yet paradoxically, we implicitly ask them to support and encourage research. The acknowledgment of this ivory tower problem has recently opened up new and exciting opportunities to open-minded scientists. The advent of digital communication technologies, mobile devices and Web 2.0 is fostering a new kind of relation between professional scientists and dedicated volunteers or participants.

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