Evaluating mobile-based data collection for crowdsourcing behavioral research

Authors: DT Esch, N Mylonopoulos, V Theoharakis

Published: 2025

Publication: Behavior Research Methods, 2025 - Springer

Mobile-based responses via platforms like Pollfish are comparable in quality to computer-based ones from MTurk and Prolific, though attentiveness varies significantly across platforms and is influenced by factors like incentives, distractions, and system 1 thinking.

Methods: Conducted two studies distributing the same survey across MTurk, Prolific, Pollfish, and Qualtrics panels to compare data quality and analyze attentiveness scores.

Key Findings: Attentiveness, device usage (mobile vs. computer), and factors influencing data quality such as incentives, respondent activity, distractions, and survey familiarity.

Limitations: Possible bias due to reliance on specific platforms, attentiveness measures may not generalize beyond tested scales, and limited exploration of non-crowdsourcing populations.

Institution: University of Cologne, University of Piraeus, Aristotle University of Thessaloniki

Research Area: Crowdsourcing Behavioral Research, Mobile Data Collection

Discipline: Behavioral Research

Citations: 1