Gay men in china develop shared strategies to spot deception on dating apps
Navigating Deception on Gay Dating Apps: A Qualitative Study of Users' Experiences, Verification Strategies, and Community Knowledge in China
Human-Computer Interaction
Summary
Using gay dating apps can sometimes be tricky because people might lie or trick each other. The authors talk with gay men in China who use these apps and learn what kinds of fake stories or scams they face. These men also develop ways to spot liars, like paying attention to how fast someone responds or noticing signs of financial scams. Importantly, the authors show that users don’t just rely on their own judgment but share tips and stories with each other in their community to stay safe.
What this means in practice
- •For mobile app developers: Design dating apps to support community sharing of user experiences to improve trust without relying solely on individual verification.
- •For online community managers: Create features that encourage users to collectively record and learn from deceptive behaviors to enhance group safety and awareness.
Authors
Yibo Meng, Lyumanshan Ye, Bingyi Liu, Huidi Lu, Xiaolan Ding
Abstract
Gay dating applications have become essential platforms for sexual minority men to seek relationships, intimacy, and community, yet they also expose users to a range of deceptive interactions that remain underexplored in HCI and CSCW research. This study examines how gay male users in China experience, identify, and respond to deception on dating applications. Through semi-structured interviews with 22 participants who used platforms such as Blued, Aloha, Fanka, and Soul, we identify a typology of deceptive practices that users encounter, including relational misrepresentation for sexual access, sustained emotional deception, financial fraud, marketing behavior disguised as ordinary users, and false identity construction. We further analyze the verification and coping strategies that users develop through long-term platform use, such as judging relational intent through interactional pace, identifying financial risk signals, recognizing commercial promotion accounts, and progressively verifying identity authenticity. Finally, we show that risk recognition is not merely an individual capacity but a collaborative practice that gradually emerges through the circulation of experience within the community, the summarization of recurrent deceptive tactics, and the learning of shared rules. Our findings contribute to CSCW scholarship by demonstrating how users of a marginalized community collectively construct practical knowledge about deception, and by revealing that trust assessment on dating platforms operates as a layered, probabilistic, and socially distributed process rather than a binary judgment.