Finding Love in the Black Box: Algorithm Awareness on Dating Apps - Data Files

METHOD A survey was conducted among 216 users of U.S.-based Tinder and 500 users of the Dutch dating app Breeze. Relationships were estimated with structural equation modeling, and effect sizes were compared between these two groups of users to assess variability based on dating app affordances. Higher algorithm awareness was associated with more trust in the recommender system, which in turn positively related to the ease by which users could find matches.

The dataset is a composite of two separate collections. The data among Breeze users was collected in collaboration with Breeze itself. Users received a popup in the app with the link to the survey. 688 people participated, which resulted in 500 complete responses in two days.

The data for Tinder users was collected in a period of several weeks on various unrelated social media pages. After 500 respondents started the survey, 216 complete responses remained. All participants had to be over 18 years old, and had to have used the app in the previous 30 days.

RESULT The presence of this fully mediated effect between awareness and satisfaction with matches suggested that knowledge of matching algorithms can affect both the perception of the recommender system as well as the results of using dating apps. In other words, users with higher algorithm awareness are more content with the quality of the profiles they match with, mediated by a higher trust in the abilities of matching algorithms.

No significant differences were found between groups. CONCLUSION Overall, the results indicate that increasing the awareness that users have of algorithm functioning could improve the online dating experience. This research contributes to the limited literature on human-AI interaction in the context of dating apps.