How to choose a life partner? A non-intuitive approach.
Qualities that grab our attention, especially physical attractiveness, doesn't predict romantic happiness. A person becomes more attractive if it is fun talking to them.
1.1. The grand experiment on romantic happiness:
Canadian scientist, Samantha Joel recruited every professor she could find who had collected data on relationships—her team ended up including 85 other scientists—and was able to build a dataset of 11,196 couples.
For each couple, Joel and her team of researchers had measures of how happy each partner reported being in their relationship. And they had data on just about anything you could think to measure about the two people in that relationship.
The researchers had data on:
Demographics (e.g., age, education, income, and race)
Physical appearance (e.g., How attractive did other people rate each partner?)
Sexual tastes (e.g., How frequently did each partner want sex? How freaky did they want that sex to be?)
Interests and hobbies
Mental and physical health
Values (e.g., their views on politics, relationships, and child-rearing)
Joel and some of the other researchers had mastered machine learning to detect subtle patterns in a large amount of data. It was among the first studies to utilize these advanced techniques to try to predict relationship happiness. They combined data from more than ten thousand couples, and utilized state-of-the-art machine learning models to help people pick better romantic partners.
The most surprising lesson is how unpredictable relationships seem to be. Joel and her coauthors found that the demographics, preferences, and values of two people had surprisingly little power in predicting whether those two people were happy in a romantic relationship.
In truth, there are important lessons in Joel and her coauthors’ machine learning project. They did find a few variables in a mate that at least slightly increase the odds you will be happy with them. The surprising difficulty in predicting romantic success has counterintuitive implications for how we should pick romantic partners. Joel and her coauthors found that many of the traits that are most competed for in the dating market do not correlate with romantic happiness.
1.2. Rise of online dating:
The findings from the research on romantic desirability, unlike the research on romantic happiness, has been definitive. Data scientists have found it strikingly easy to detect the qualities that are desired in the dating scene.
The major development in the search for romance in the early part of the twenty-first century has been the rise of online dating. However, the use of online dating has since exploded. By 2017, nearly 40 percent of couples met online. And this number continues to rise every year.
In this century, researchers have better ways to figure out what people desire in a partner than merely asking them. Researchers around the world have mined data from OkCupid, eHarmony, match dot com, Hinge, and other matching services to determine how much just about every factor contributes to one’s desirability in the dating market.
1.3. Attractiveness in romantic relationships:
A team of researchers—Günter J. Hitsch, Ali Hortaçsu, and Dan Ariely— studied thousands of heterosexual users of an online dating site. Each user of the site included photos, and the researchers recruited and paid a different group of people to rate the attractiveness of every user on a scale of 1 to 10. They measured desirability based on how many unsolicited messages a person received and how frequently their messages were responded to.
The researchers found that looks matter. A lot.
Roughly 30 percent of how well a female heterosexual dater performed on the site could be explained by their looks. Heterosexual women are a little less shallow but still plenty shallow. About 18 percent of male heterosexual daters’ success could be explained by their looks. Beauty, it turns out, is, for both sexes, the most important predictor of how many potential partners message and respond to one’s messages in online dating.
However, Joel and her coauthors found, in their study of more than 11,000 long-term couples, that the conventional attractiveness of one’s partner does not predict romantic happiness. Similarly, tall men, men with sexy occupations, people of certain races, and people who remind others of themselves are valued tremendously in the dating market. Such qualities immediately grab our attention. Just about all of us are quickly drawn to the conventionally beautiful, for example. But these attention-grabbing, shiny qualities, the data suggests, make no difference to our long-term romantic happiness.
1.4. How to eliminate attractiveness bias?
One important, relevant, fascinating, and data-driven finding was uncovered by researchers at the University of Texas. In the beginning of a course, the professors asked all the heterosexual students in that course to rate the attractiveness of each of their opposite-sex classmates. Not surprisingly, there was a good deal of consensus. Most people picked the same classmates as the most attractive; these people were, by definition, conventionally attractive.
At the end of the course, professors again asked the students to rate the attractiveness of each of their opposite-sex classmates. This is where the study got interesting. Now there was more disagreement in the attractiveness ratings. At the end of the class, people were far more likely to rate a person that other people didn’t find so attractive as the most attractive.
When two people involved, don’t enjoy talking to each other, attractiveness decreases. A person may have seemed attractive in the beginning but they became more attractive if they enjoy talking.
The research suggests that we might overrule our initial lack of attraction. Physical attraction, research shows, can grow over time if we like a person (or disappear over time if we don’t like a person). The data suggests we should go on more dates with undervalued assets (those who might not have the qualities that so many people find so alluring) even if we don’t initially find them attractive—and be patient, allowing a potential attraction to grow.
1.5. It’s all about YOU: The Data Science Says
Researchers asked these questions to the people involved in romantic relationships and used this information to predict relationship happiness.
How satisfied were you with your life before you met the person x?
Were you free from depression before you met the person x?
found that people who answered “yes” to questions such as these are significantly more likely to report being happy in their romantic relationship. How a person answered questions about themselves was roughly four times more predictive of their relationship happiness than all the traits of their romantic partner combined. ****
“Nobody can make you happy until you’re happy with yourself first.”
One’s own happiness outside a relationship is by far the biggest predictor of one’s happiness in a romantic relationship. If not conventional attractiveness, what are the qualities that do?
1.6. What qualities of a mate are predictive of romantic happiness?
The Most Likely Best Mate: Someone Satisfied with Life, Secure with Who They Are, Who Conscientiously Tries to Better Themselves:
Joel and her coauthors research suggests that
People who can trust others and are trustworthy,
Have an easier time being intimate with others.
Comfortable expressing interest and affection,
Conscientious people (NOT consciousness), who are disciplined, efficient, organized, reliable (Conscientiousness is one of the big 5 personality traits).
People who have a growth mindset, who tend to believe they can improve their talents and abilities through hard work and persistence.
Such people may work to become better romantic partners.
1.7. When to come out of a relationship?
What do couples that get better over time tend to have in common? What about those that get worse?
Joel and her coauthors’ models had virtually no predictive power in predicting changes in romantic happiness. Happy couples are more likely to be happy in the future. Unhappy couples are more likely to be unhappy in the future. But there is nothing else about the two people that could improve predictions about future happiness.
Many people make romantic decisions based on projected changes in happiness. How many times has one of your friends stayed in a relationship in which they weren’t happy because they think, on paper, they should be happy—and eventually will be happy? “Sure, I’m miserable now,” the friend might say. “But this relationship should work. It has to get better.”
The results suggest that people are largely making a mistake when they expect their happiness in a relationship to change based on various qualities of them and their partner. The friend who stays in a relationship in which he is unhappy because he thinks he and his partner have so much in common and will eventually be happy is making a mistake.
Reference: Summary of book Don't Trust Your Gut: Using Data to Get What You Really Want in LIfe (Chapter 1)
Interesting