Familiarity Breeds Trust? The Relationship between Dating App Use and Trust in Dating Algorithms via Algorithm Awareness and Critical Algorithm Perceptions

Abstract

Previous studies have suggested that dating app use can foster acceptance of the controversial idea of algorithm matchmaking. However, an integrated framework to explain this relationship is lacking. To address this gap, this study proposes a familiarity-breeds-trust hypothesis, which suggests that dating app use can increase trust in dating algorithms by raising algorithm awareness and enhancing perceived agency. To test this hypothesis, the current work employed an exploratory sequential mixed-methods design. Study 1 interviewed 19 dating app users and identified four types of critical algorithm perceptions that reflected perceived threats to user agency. Study 2 surveyed 371 users of Tantan—a mainstream Chinese dating app that resembles Tinder—and found a positive relationship between Tantan use and trust in dating algorithms. Additionally, Tantan use was positively related to algorithm awareness, which was negatively related to critical algorithm perceptions. Furthermore, critical algorithm perceptions negatively predicted trust in dating algorithms. The findings provide support for the familiarity-breeds-trust hypothesis. Theoretical implications for future human-algorithm interaction studies and practical suggestions are also discussed.

Keywords:

• Algorithm awareness
• dating app
• trust
• perception

Acknowledgments

We would like to thank the editors and anonymous reviewers for their valuable feedback to an earlier version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Data availability statement

The data that support the findings of this study are available upon reasonable request from the corresponding author. The data are not publicly available due to their containing information that could compromise the privacy of research participants.

Additional information

Funding

Data collection was conducted at Nanjing University and received financial support from the Zhuoyue Graduate Fellowship granted by the School of Journalism and Communication, Nanjing University.

Notes on contributors

Junwen Hu

Junwen Hu is a PhD student at the Department of Communication at Michigan State University. He studies interpersonal communication, elective relationships, and social support.

Rui Wang

Rui Wang is a PhD student in the Department of Communication at University at Buffalo-SUNY. She studies media effects, political communication and misinformation using computational methods and experimental design.