Online dating has transformed the way people meet and start relationships. However, online dating platforms typically have many lurkers without active participation. Using a self-regulation framework, this paper aims to study users' active participation in online dating through a mixed methods study. We first conducted qualitative and quantitative investigations with a machine learning method to explore user active participation and its antecedents. We then developed a theoretical model and conducted a statistical analysis of the model. The empirical findings showed that service quality and trust significantly affected individual active participation in a dating site through attachments to the daters and services. The findings of the study contribute to the extant literature by analyzing user participation in online dating from an attachment perspective.
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