Insights from an experiment crowdsourcing data from thousands of US Amazon users: The importance of transparency, money, and data use

TL;DR

This study demonstrates that transparency and monetary incentives significantly increase user data sharing in crowdsourcing efforts, revealing demographic influences and insights into privacy perceptions, with implications for ethical data collection.

Contribution

The paper introduces an innovative, ethically designed crowdsourcing method for collecting extensive user purchase data, and empirically evaluates factors influencing data sharing and privacy attitudes.

Findings

Monetary incentives greatly increase data sharing, especially in real scenarios.

Demographics like age, gender, and education significantly influence sharing behavior.

Participants' opinions on data use vary by context and demographic factors.

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 5000 US users. We developed a data collection tool that prioritizes participant consent and includes an experimental study design. The design allows us to study multiple aspects of privacy perception and data sharing behavior. Experiment results (N=6325) 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 demographics 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.