Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
Jon Levy1, Devin Markell2, Moran Cerf1,3
1Kellogg School of Management, Northwestern University, Evanston, IL, United States.
Frontiers in Psychology
|September 26, 2019
Summary
Similarity in psychological traits, physical attributes, and personal choices drives effective matching on dating apps. Introverts, however, rarely match effectively with other introverts.
Area of Science:
- Computational Social Science
- Human-Computer Interaction
- Relationship Science
Background:
- Online dating platforms facilitate millions of connections.
- Understanding factors influencing successful matches is crucial for user experience and platform design.
Purpose of the Study:
- To identify characteristics of effective matching on a large-scale mobile dating application.
- To analyze user decision-making processes in partner selection.
Main Methods:
- Analysis of a dataset of over 421 million potential matches.
- Application of a biologically inspired choice model to predict user decisions.
- Examination of trait similarity, user choices, and response times.
Main Results:
- High similarity in psychological traits (e.g., extroversion), physical traits (e.g., height), and personal choices (e.g., relationship type) correlates with effective matching.
- Introverts showed a low likelihood of effective matching with other introverts.
- A choice model predicted selection and response time with nearly 60% accuracy.
Conclusions:
- Users tend to prefer partners with shared attributes, with similarity increasing the likelihood of meeting.
- Initial partner preferences may be less selective, converging towards similarity during conversation.
- User decision-making in online dating involves rapid initial selections and a gradual convergence on compatible partners.
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