Popularity Feedback and Adaptation Strategies in Online Dating: A Social Comparison Perspective

In stock
SKU
49.2.05

Publication History

Received: November 15, 2021
Revised: October 18, 2022; August 27, 2023; June 20, 2024
Accepted: August 12, 2024
Published in Issue: June 1, 2025

https://doi.org/10.25300/MISQ/2024/17861 

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Abstract

Digital platforms are increasingly employing informational nudges to motivate user participation. This paper examines the provision of popularity information as a feedback mechanism and its impact on users’ adaptation strategies. Leveraging ego utility theory and self-determination theory, we hypothesize that comparative popularity information—information that facilitates social comparison—will trigger different reactions based on gender and popularity level. In collaboration with an online dating service provider, we designed and conducted two randomized field experiments in which we provided popularity feedback to platform users and investigated their post-feedback behavioral changes in two adaptation strategies: the selectiveness in choosing potential partners (i.e., selectivity calibration) and the frequency of their online profile modifications (i.e., self-marketing). In the first experiment, where we revealed information about their popularity relative to other users, we found that those who received low-popularity feedback significantly increased self-marketing efforts and lowered their selectivity, but the opposite was observed in individuals who received high-popularity feedback. We also found that men readily made adaptations to their selectivity calibration and self-marketing, whereas women’s behaviors were more persistent as they exhibited little strategic change. We then conducted a second experiment in which we revealed absolute popularity instead of comparative popularity and observed no significant changes in adaptation strategies. Comparing the outcomes of the two experiments, we argue that it is the social comparison information associated with comparative popularity that drives user behavioral changes.

Additional Details
Author Lanfei Shi, Peng Huang, and Jui Ramaprasad
Year 2025
Volume 49
Issue 2
Keywords Popularity feedback, comparative feedback, social comparison, two-sided platforms, matching markets, online dating, gender difference, randomized field experiments
Page Numbers 521-554
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