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Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences

Leveraging a massive dataset of over 421 million potential matches between single users on a leading mobile dating application, we were able to identify numerous characteristics of effective matching. Effective matching is defined as the exchange of contact information with the likely intent to meet...

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Detalles Bibliográficos
Autores principales: Levy, Jon, Markell, Devin, Cerf, Moran
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743509/
https://www.ncbi.nlm.nih.gov/pubmed/31551868
http://dx.doi.org/10.3389/fpsyg.2019.02010
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author Levy, Jon
Markell, Devin
Cerf, Moran
author_facet Levy, Jon
Markell, Devin
Cerf, Moran
author_sort Levy, Jon
collection PubMed
description Leveraging a massive dataset of over 421 million potential matches between single users on a leading mobile dating application, we were able to identify numerous characteristics of effective matching. Effective matching is defined as the exchange of contact information with the likely intent to meet in person. The characteristics of effective match include alignment of psychological traits (i.e., extroversion), physical traits (i.e., height), personal choices (i.e., desiring the same relationship type), and shared experiences. For nearly all characteristics, the more similar the individuals were, the higher the likelihood was of them finding each other desirable and opting to meet in person. The only exception was introversion, where introverts rarely had an effective match with other introverts. When investigating the preliminary stages of the choice process we looked at the consistency between the choice of men/women, the time it took users to make these binary choices, and the tendency of yes/no decisions. We used a biologically inspired choice model to estimate the decision process and could predict the selection and response time with nearly 60% accuracy. Given that people make their initial selection in no more than 11 s, and ultimately prefer a partner who shares numerous attributes with them, we suggest that users are less selective in their early preferences and gradually, during their conversation, converge onto clusters that share a high degree of similarity in characteristics.
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spelling pubmed-67435092019-09-24 Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences Levy, Jon Markell, Devin Cerf, Moran Front Psychol Psychology Leveraging a massive dataset of over 421 million potential matches between single users on a leading mobile dating application, we were able to identify numerous characteristics of effective matching. Effective matching is defined as the exchange of contact information with the likely intent to meet in person. The characteristics of effective match include alignment of psychological traits (i.e., extroversion), physical traits (i.e., height), personal choices (i.e., desiring the same relationship type), and shared experiences. For nearly all characteristics, the more similar the individuals were, the higher the likelihood was of them finding each other desirable and opting to meet in person. The only exception was introversion, where introverts rarely had an effective match with other introverts. When investigating the preliminary stages of the choice process we looked at the consistency between the choice of men/women, the time it took users to make these binary choices, and the tendency of yes/no decisions. We used a biologically inspired choice model to estimate the decision process and could predict the selection and response time with nearly 60% accuracy. Given that people make their initial selection in no more than 11 s, and ultimately prefer a partner who shares numerous attributes with them, we suggest that users are less selective in their early preferences and gradually, during their conversation, converge onto clusters that share a high degree of similarity in characteristics. Frontiers Media S.A. 2019-09-06 /pmc/articles/PMC6743509/ /pubmed/31551868 http://dx.doi.org/10.3389/fpsyg.2019.02010 Text en Copyright © 2019 Levy, Markell and Cerf. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Psychology
Levy, Jon
Markell, Devin
Cerf, Moran
Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title_full Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title_fullStr Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title_full_unstemmed Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title_short Polar Similars: Using Massive Mobile Dating Data to Predict Synchronization and Similarity in Dating Preferences
title_sort polar similars: using massive mobile dating data to predict synchronization and similarity in dating preferences
topic Psychology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6743509/
https://www.ncbi.nlm.nih.gov/pubmed/31551868
http://dx.doi.org/10.3389/fpsyg.2019.02010
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