LIONESS Lab: a free web-based platform for conducting interactive experiments online

Giamattei, Marcus; Yahosseini, Kyanoush Seyed; Gächter, Simon; Molleman, Lucas

doi:10.1007/s40881-020-00087-0

Cited by 94 publications

(44 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Background variables such as the Raven SPM (estimated IQ) and several questionnaires (not relevant to the current study) were administered online using Qualtrics ( www.qualtrics.com ). In a separate session the DG, UG, and learning tasks were completed using the online software LIONESS Lab 65 .…”

Section: Methodsmentioning

confidence: 99%

Developmental asymmetries in learning to adjust to cooperative and uncooperative environments

Westhoff

Molleman

Viding

et al. 2020

Sci Rep

Self Cite

View full text Add to dashboard Cite

Learning to successfully navigate social environments is a critical developmental goal, predictive of long-term wellbeing. However, little is known about how people learn to adjust to different social environments, and how this behaviour emerges across development. Here, we use a series of economic games to assess how children, adolescents, and young adults learn to adjust to social environments that differ in their level of cooperation (i.e., trust and coordination). Our results show an asymmetric developmental pattern: adjustment requiring uncooperative behaviour remains constant across adolescence, but adjustment requiring cooperative behaviour improves markedly across adolescence. Behavioural and computational analyses reveal that age-related differences in this social learning are shaped by age-related differences in the degree of inequality aversion and in the updating of beliefs about others. Our findings point to early adolescence as a phase of rapid change in cooperative behaviours, and highlight this as a key developmental window for interventions promoting well-adjusted social behaviour.

show abstract

Section: Methodsmentioning

confidence: 99%

Developmental asymmetries in learning to adjust to cooperative and uncooperative environments

Westhoff

Molleman

Viding

et al. 2020

Sci Rep

Self Cite

View full text Add to dashboard Cite

show abstract

“…Our experimental data analysis and modeling software pipelines are complementary to current efforts to build configurable software platforms to perform social science experiments. See [35][36][37][38]. Usually, these systems only focus on the design and running of online lab experiments.…”

Section: Plos Onementioning

confidence: 99%

“…implement a web-based public goods experiment, and to recruit participants around the world. In [63], a repeated public goods experiment was implemented in the free web-based platform for interactive online experiments, LIONESS [36], and participants were recruited via Amazon Mechanical Turk (MTurk). In [37] a modular virtual lab named Empirica offers a development platform for virtual lab experiments, and they claim that is even accessible to novice programmers.…”

Section: Plos Onementioning

confidence: 99%

“…Another limitation, and an opportunity for future work, is to provide a data specification for both experiments and analyses. Specifically, Section 2.1 identified experimental platforms that are customizable [35][36][37][38] in ways that are analogous to our approach for customizable software analysis pipelines. A single specification language for experiments and analyses could be used to coordinate experiments and analyses.…”

Section: Conclusion Future Work and Limitationsmentioning

confidence: 99%

See 1 more Smart Citation

Data analysis and modeling pipelines for controlled networked social science experiments

Cedeno-Mieles

Ren

et al. 2020

PLoS ONE

View full text Add to dashboard Cite

There is large interest in networked social science experiments for understanding human behavior at-scale. Significant effort is required to perform data analytics on experimental outputs and for computational modeling of custom experiments. Moreover, experiments and modeling are often performed in a cycle, enabling iterative experimental refinement and data modeling to uncover interesting insights and to generate/refute hypotheses about social behaviors. The current practice for social analysts is to develop tailor-made computer programs and analytical scripts for experiments and modeling. This often leads to inefficiencies and duplication of effort. In this work, we propose a pipeline framework to take a significant step towards overcoming these challenges. Our contribution is to describe the design and implementation of a software system to automate many of the steps involved in analyzing social science experimental data, building models to capture the behavior of human subjects, and providing data to test hypotheses. The proposed pipeline framework consists of formal models, formal algorithms, and theoretical models as the basis for the design and implementation. We propose a formal data model, such that if an experiment can be described in terms of this model, then our pipeline software can be used to analyze data efficiently. The merits of the proposed pipeline framework is elaborated by several case studies of networked social science experiments.

show abstract

“…Other popular platforms: ConG(Pettit, Friedman, Kephart, & Oprea, 2014), LIONESS Lab(Giamattei, Molleman, Yahosseini, & Gächter, 2019), MWERT(Hawkins, 2015), nodeGame(Balietti, 2017), Psynteract(Henninger, Kieslich, & Hilbig, 2017), SoPHIE(Hendriks, 2012), and TurkServer(Mao, Chen, Parkes, & Procaccia, 2012).…”

mentioning

confidence: 99%

How to implement real-time interaction between participants in online surveys: A practical guide to SMARTRIQS

Molnár¹

2019

Preprint

View full text Add to dashboard Cite

While online experimentation is becoming increasingly popular in psychology, implementing real-time interaction between participants in online studies remains uniquely challenging, as it requires researchers to have advanced programming skills, or to purchase expensive third-party services. These challenges prevent many psychologists and other social scientists from utilizing online methods when they wish to study a vast array of social behaviors and interpersonal decision-making. SMARTRIQS is a free and open-source application that fills in this crucial gap in contemporary experimental research methods. SMARTRIQS offers researchers the ability to design surveys that feature real-time interaction between participants—including live text chat—without requiring re-searchers to learn any programming language, install any software, or pay for any third-party services. This paper provides researchers a practical guide to SMARTRIQS and shows them howto turn regular (non-interactive) online surveys into fully interactive experiments. The paper not only provides a comprehensive guide to designing interactive studies in SMARTRIQS in general but also walks readers through the step-by-step instructions for setting up a particular study (Dictator Game with chat). The tutorial starts from the very basics, assuming no prior expertise in online experimentation, and is accessible to everyone, even those who are less—or not at all—familiar with Qualtrics.

show abstract

LIONESS Lab: a free web-based platform for conducting interactive experiments online

Cited by 94 publications

References 34 publications

Developmental asymmetries in learning to adjust to cooperative and uncooperative environments

Developmental asymmetries in learning to adjust to cooperative and uncooperative environments

Data analysis and modeling pipelines for controlled networked social science experiments

How to implement real-time interaction between participants in online surveys: A practical guide to SMARTRIQS

Contact Info

Product

Resources

About