Matchmaking companies and theoretical perspectives on close relationships suggest that initial attraction is, to some extent, a product of two people’s self-reported traits and preferences. We used machine learning to test how well such measures predict people’s overall tendencies to romantically desire other people (actor variance) and to be desired by other people (partner variance), as well as people’s desire for specific partners above and beyond actor and partner variance (relationship variance). In two speed-dating studies, romantically unattached individuals completed more than 100 self-report measures about traits and preferences that past researchers have identified as being relevant to mate selection. Each participant met each opposite-sex participant attending a speed-dating event for a 4-min speed date. Random forests models predicted 4% to 18% of actor variance and 7% to 27% of partner variance; crucially, however, they were unable to predict relationship variance using any combination of traits and preferences reported before the dates. These results suggest that compatibility elements of human mating are challenging to predict before two people meet.
BreimanL. (2001). Random forests. Machine Learning, 45, 5–32.
2.
BussD. M.BarnesM. (1986). Preferences in human mate selection. Journal of Personality and Social Psychology, 50, 559–570.
3.
ByrneD. (1961). Interpersonal attraction and attitude similarity. The Journal of Abnormal and Social Psychology, 62, 713–715.
4.
CampbellL.ChinK.StantonS. C. E. (2016). Initial evidence that individuals form new relationships with partners that more closely match their ideal preferences. Collabra, 2, 2–7.
5.
EastwickP. W. (2016). The emerging integration of close relationships research and evolutionary psychology. Current Directions in Psychological Science, 25, 183–190.
6.
EastwickP. W.HardenK. P.ShukuskyJ. A.MorganT. A.JoelS. (2017). Consistency and inconsistency among romantic partners over time. Journal of Personality and Social Psychology, 112, 838–885.
7.
EastwickP. W.HuntL. L. (2014). Relational mate value: Consensus and uniqueness in romantic evaluations. Journal of Personality and Social Psychology, 106, 728–751.
8.
EastwickP. W.LuchiesL. B.FinkelE. J.HuntL. L. (2014). The predictive validity of ideal partner preferences: A review and meta-analysis. Psychological Bulletin, 140, 623–665.
9.
FinkelE. J.BurnetteJ. L.ScissorsL. E. (2007). Vengefully ever after: Destiny beliefs, state attachment anxiety, and forgiveness. Journal of Personality and Social Psychology, 92, 871–886.
10.
FinkelE. J.EastwickP. W.KarneyB. R.ReisH. T.SprecherS. (2012). Online dating: A critical analysis from the perspective of psychological science. Psychological Science in the Public Interest, 13, 3–66.
11.
FinkelE. J.EastwickP. W.MatthewsJ. (2007). Speed-dating as an invaluable tool for studying romantic attraction: A methodological primer. Personal Relationships, 14, 149–166.
12.
FletcherG. J. O.SimpsonJ. A.CampbellL.OverallN. C. (2015). Pair-bonding, romantic love, and evolution: The curious case ofHomo sapiens. Perspectives on Psychological Science, 10, 20–36.
13.
FletcherG. J. O.SimpsonJ. A.ThomasG.GilesL. (1999). Ideals in intimate relationships. Journal of Personality and Social Psychology, 76, 72–89.
14.
GableS. L.GonzagaG. C.StrachmanA. (2006). Will you be there for me when things go right? Supportive responses to positive event disclosures. Journal of Personality and Social Psychology, 91, 904–917.
15.
GableS. L.ImpettE. A. (2012). Approach and avoidance motives and close relationships. Social & Personality Psychology Compass, 6, 95–108.
16.
GenuerR.PoggiJ. M.Tuleau-MalotC. (2010). Variable selection using random forests. Pattern Recognition Letters, 31, 2225–2236.
17.
GenuerR.PoggiJ. M.Tuleau-MalotC. (2016). VSURF: Variable selection using random forests (Version 1.0.3) [Computer software]. Retrieved from https://cran.r-project.org/package=VSURF
18.
HewittJ. K. (2012). Editorial policy on candidate gene association and candidate gene-by-environment interaction studies of complex traits. Behavior Genetics, 42, 1–2.
19.
ImpettE. A.GableS. L.PeplauL. A. (2005). Giving up and giving in: The costs and benefits of daily sacrifice in intimate relationships. Journal of Personality and Social Psychology, 89, 327–344.
20.
JoelS.TeperR.MacDonaldG. (2014). People overestimate their willingness to reject potential romantic partners by overlooking their concern for others. Psychological Science, 25, 2233–2240.
21.
KarneyB. R.BradburyT. N. (1995). The longitudinal course of marital quality and stability: A review of theory, methods, and research. Psychological Bulletin, 118, 3–34.
KennyD. A.KashyD. A.CookW. L. (2006). Dyadic data analysis. New York, NY: Guilford Press.
24.
Kiecolt-GlaserJ. K.NewtonT. L. (2001). Marriage and health: His and hers. Psychological Bulletin, 127, 472–503.
25.
KirkpatrickL. A.DavisK. E. (1994). Attachment style, gender, and relationship stability: A longitudinal analysis. Journal of Personality and Social Psychology, 66, 502–512.
26.
KumashiroM.FinkelE. J.RusbultC. E. (2002). Self-respect and pro-relationship behavior in marital relationships. Journal of Personality, 70, 1009–1049.
27.
LaurenceauJ. P.BarrettL. F.PietromonacoP. R. (1998). Intimacy as an interpersonal process: The importance of self-disclosure, partner disclosure, and perceived partner responsiveness in interpersonal exchanges. Journal of Personality and Social Psychology, 74, 1238–1251.
28.
LeB.DoveN. L.AgnewC. R.KornM. S.MutsoA. A. (2010). Predicting nonmarital romantic relationship dissolution: A meta-analytic synthesis. Personal Relationships, 17, 377–390.
29.
LiN. P.YongJ. C.TovW.SngO.FletcherG. J. O.ValentineK. A.. . . BallietD. (2013). Mate preferences do predict attraction and choices in the early stages of mate selection. Journal of Personality and Social Psychology, 105, 757–776.
30.
LiawA.WienerM. (2015). randomForest: Breiman and Cutler’s random forests for classification and regression (Version 4.6-12) [Computer software]. Retrieved from https://cran.r-project.org/package=randomForest
31.
LuoS.ZhangG. (2009). What is attractive: Similarity, reciprocity, security or beauty? Evidence from a speed-dating study. Journal of Personality, 77, 933–964.
32.
McClureM. J.LydonJ. E.BacusJ. R.BaldwinM. W. (2010). A signal detection analysis of chronic attachment anxiety at speed dating: Being unpopular is only the first part of the problem. Personality and Social Psychology Bulletin, 36, 1024–1036.
33.
McNultyJ. K. (2016). Should spouses be demanding less from marriage? A contextual perspective on the implications of interpersonal standards. Personality and Social Psychology Bulletin, 42, 444–457.
34.
MontoyaR. M. (2008). I’m hot, so I’d say you’re not: The influence of objective physical attractiveness on mate selection. Personality and Social Psychology Bulletin, 34, 1315–1331.
35.
MurrayS. L.HolmesJ. G.CollinsN. L. (2006). Optimizing assurance: The risk regulation system in relationships. Psychological Bulletin, 132, 641–666.
36.
OkbayA.BeauchampJ. P.FontanaM. A.LeeJ. J.PersT. H.RietveldC. A.. . . BenjaminD. J. (2016). Genome-wide association study identifies 74 loci associated with educational attainment. Nature, 533, 539–542.
37.
R Development Core Team. (2016). R: A language and environment for statistical computing (Version 3.3.2) [Computer software]. Retrieved from https://www.r-project.org/index.html
38.
RusbultC. E.Van LangeP. A. M. (2003). Interdependence, interaction, and relationships. Annual Review of Psychology, 54, 351–375.
39.
SilverN. (2012). The signal and the noise: Why so many predictions fail – but some don’t. New York, NY: Penguin Press.
40.
SimpsonJ. A.GangestadS. W. (1991). Individual differences in sociosexuality: Evidence for convergent and discriminant validity. Journal of Personality and Social Psychology, 60, 870–883.
41.
SpielmannS. S.MacDonaldG.MaxwellJ. A.JoelS.PeragineD.MuiseA.ImpettE. A. (2013). Settling for less out of fear of being single. Journal of Personality and Social Psychology, 105, 1049–1073.
42.
StroblC.MalleyJ.TutzG. (2009). An introduction to recursive partitioning: Rationale, application, and characteristics of classification and regression trees, bagging, and random forests. Psychological Methods, 14, 323–348.
43.
TidwellN. D.EastwickP. W.FinkelE. J. (2013). Perceived, not actual, similarity predicts initial attraction in a live romantic context: Evidence from the speed-dating paradigm. Personal Relationships, 20, 199–215.
44.
WeigelD.MurrayC. (2000). The paradox of stability and change in relationships: What does chaos theory offer for the study of romantic relationships?Journal of Social and Personal Relationships, 17, 425–449.
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