Opendata, web and dolomites


A data-driven, multivariate approach to human mate preferences.

Total Cost €


EC-Contrib. €






Project "MULTIPREF" data sheet

The following table provides information about the project.


Organization address
postcode: G12 8QQ

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country United Kingdom [UK]
 Total cost 183˙454 €
 EC max contribution 183˙454 € (100%)
 Programme 1. H2020-EU.1.3.2. (Nurturing excellence by means of cross-border and cross-sector mobility)
 Code Call H2020-MSCA-IF-2015
 Funding Scheme MSCA-IF-EF-ST
 Starting year 2017
 Duration (year-month-day) from 2017-01-01   to  2018-12-31


Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITY OF GLASGOW UK (GLASGOW) coordinator 183˙454.00


 Project objective

Human mate preferences can provide important insight into human social and sexual relationships; however, to date research on human mate preferences are typically based on sexual selection models derived from studies of non-human species to identify candidate characteristics that may influence preferences, and then studies only assess one or two of these characteristics at a time. This is problematic as this does not reflect the multivariate nature of human mate choice in reality. To address these limitations, I propose a research project that uses data-driven approaches to identify characteristics important to human mate preferences that entirely avoids the problem of selecting candidate characteristics based on inappropriate theoretical models. I also propose using powerful new computational methods to develop the first multivariate model of human mate preferences. First, I will use state-of-the-art statistical techniques developed in evolutionary biology to identify facial, body, and personality characteristics important for human mate preferences. Once these characteristics have been identified, they will be used as input into a large, iterative, online study using a technique that simulates the effects of Darwinian evolution on preferences. This project directly addresses difficulties in the field and will develop the first multivariate model of human mate preferences that will drive future research in the field.


year authors and title journal last update
List of publications.
2018 Anthony J. Lee, Lisa M. DeBruine, Benedict C. Jones
Individual-specific mortality is associated with how individuals evaluate future discounting decisions
published pages: 20180304, ISSN: 0962-8452, DOI: 10.1098/rspb.2018.0304
Proceedings of the Royal Society B: Biological Sciences 285/1880 2019-10-08
2017 Anthony J. Lee, Margaret J. Wright, Nicholas G. Martin, Matthew C. Keller, Brendan P. Zietsch
Facial Trustworthiness is Associated with Heritable Aspects of Face Shape
published pages: 351-364, ISSN: 2198-7335, DOI: 10.1007/s40750-017-0073-0
Adaptive Human Behavior and Physiology 3/4 2019-10-08
2017 Anthony J. Lee, Courtney Hibbs, Margaret J. Wright, Nicholas G. Martin, Matthew C. Keller, Brendan P. Zietsch
Assessing the accuracy of perceptions of intelligence based on heritable facial features
published pages: 1-8, ISSN: 0160-2896, DOI: 10.1016/j.intell.2017.06.002
Intelligence 64 2019-10-08
2019 Anthony J. Lee, Benedict C. Jones, Lisa M. DeBruine
Investigating the association between mating-relevant self-concepts and mate preferences through a data-driven analysis of online personal descriptions
published pages: , ISSN: 1090-5138, DOI: 10.1016/j.evolhumbehav.2019.01.005
Evolution and Human Behavior 2019-09-02

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The information about "MULTIPREF" are provided by the European Opendata Portal: CORDIS opendata.

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