Insights from an Experiment Crowdsourcing Data from Thousands of US Amazon Users: The importance of transparency, money, and data use

Alex Berke; Robert Mahari; Alex Pentland; Kent Larson; Dana Calacci

doi:10.1145/3687005

journal article Open Access Nov 07, 2024

Insights from an Experiment Crowdsourcing Data from Thousands of US Amazon Users: The importance of transparency, money, and data use

Alex Berke

Proceedings of the ACM on Human-Computer Interaction Vol. 8 No. CSCW2 pp. 1-48 · Association for Computing Machinery (ACM)

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Abstract

Data generated by users on digital platforms are a crucial resource for advocates and researchers interested in uncovering digital inequities, auditing algorithms, and understanding human behavior. Yet data access is often restricted. How can researchers both effectively and ethically collect user data? This paper shares an innovative approach to crowdsourcing user data to collect otherwise inaccessible Amazon purchase histories, spanning 5 years, from more than 5,000 U.S. users. We developed a data collection tool that prioritizes participant consent and includes an experimental study design. The design allows us to study multiple important aspects of privacy perception and user data sharing behavior, including how socio-demographics, monetary incentives and transparency can impact share rates. Experiment results (N=6,325) reveal both monetary incentives and transparency can significantly increase data sharing. Age, race, education, and gender also played a role, where female and less-educated participants were more likely to share. Our study design enables a unique empirical evaluation of the 'privacy paradox', where users claim to value their privacy more than they do in practice. We set up both real and hypothetical data sharing scenarios and find measurable similarities and differences in share rates across these contexts. For example, increasing monetary incentives had a 6 times higher impact on share rates in real scenarios. In addition, we study participants' opinions on how data should be used by various third parties, again finding that gender, age, education, and race have a significant impact. Notably, the majority of participants disapproved of government agencies using purchase data yet the majority approved of use by researchers. Overall, our findings highlight the critical role that transparency, incentive design, and user demographics play in ethical data collection practices, and provide guidance for future researchers seeking to crowdsource user generated data.

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Details

Published: Nov 07, 2024
Vol/Issue: 8(CSCW2)
Pages: 1-48
License: View

Authors

A

Alex Berke

MIT Media Lab, Cambridge, Massachusetts, USA

R

Robert Mahari

MIT Media Lab & Harvard Law School, Cambridge, Massachusetts, USA

A

Alex Pentland

MIT Media Lab & Stanford HAI, Cambridge, Massachusetts, USA

K

Kent Larson

MIT Media Lab, Cambridge, Massachusetts, USA

D

Dana Calacci

College of Information Sciences and Technology, Pennsylvania State University & MIT Media Lab, University Park, USA

Cite This Article

Alex Berke, Robert Mahari, Alex Pentland, et al. (2024). Insights from an Experiment Crowdsourcing Data from Thousands of US Amazon Users: The importance of transparency, money, and data use. Proceedings of the ACM on Human-Computer Interaction, 8(CSCW2), 1-48. https://doi.org/10.1145/3687005

Insights from an Experiment Crowdsourcing Data from Thousands of US Amazon Users: The importance of transparency, money, and data use

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