Data in Dating: From eHarmony to Tinder & further

Data in Dating: From eHarmony to Tinder & further

Big Data is something we are using more and more. It comes with great ideas and solutions but also with uncertainty. The idea behind analyzing data is already quite old. Ian Ayres discusses it already in 2007 in his book Super Crunchers. He discusses how quantitative analysis can be used, in a creative way, to give more insights into all different aspects of life. As data science is way more used nowadays, we will reflect upon a certain case, about eHarmony, in the Super Crunchers book. We will reflect upon the case and compare it critically with recent scientific literature. First, we will give a brief summary of the case, then we will go over the recent literature and critically evaluate the cases.

Apparently, even though the extensive questionnaire indicates a homosexual partner preference, e-Harmony refuses to match same-sex couples

Ayres (2017) discusses in Super Crunchers the case of eHarmony, a modern – this was written in 2007 – dating service that uses hidden variables to find compatible partners. The founder of eHarmony Neil Clark Warren based its business on his late 1990’s study of more than 5000 married couples. He then patented a predictive model – a regression – based on twenty-nine variables allegedly best denoting the perfect relationship: variables on emotional temperament, social style, cognitive mode and relationship skills.

Surprising to Ayres is how eHarmony dared to select the relevant predictors in the form of “hidden variables”, i.e. factors that their own customers were not aware of. As such, it may just happen that their algorithm will match you with someone you would have never imagined you liked. This effect is exacerbated also by the large volume of input data – the customers would have to fill out a 436-question form upon subscription- and the very secret nature of their predictive model.

This fact does not stop Ayres from being pleased that, although the best paradigm is unknown, dating services are competing on finding out whether their algorithm got it right as well (“validation” in modern jargon), beyond just on their matching algorithm

The competitors of eHarmony use a different paradigm in finding couples. Instead of matching you with the most similar partner, Perfectmatch and True use compatibility-based methods. Perfectmatch is bases its method on the Myers-Briggs personality test, which consists of labeling each individual into one of sixteen personality types. The relatively long record of this test and its growing popularity have also allowed for historical records that state which personality type works best with which. True calculates instead the likelihood you will get along with someone else, their model being based on 99 variables.

So, which one is better? Similarity- or compatibility-based matching? Ayres considers that data should be able to adjudicate whether similar or compatible people make the best couples. Well, the truth is no one knows. The algorithms and the data are essential to this industry and therefore kept secret, so it is hard to say. Nevertheless, e-Harmony claims that their married couples are “significantly happier” than any couple that would have met otherwise. No back-up has been found for their claim (except for Clark & Snow (2014) written by eHarmony and kept private).

Indeed, for eHarmony, the raw data and the algorithm output does not exclusively determine the final coupling decision. Unlike its competitors, e-Harmony insists on matching couples based on similarity, and yet ironically when it comes to gender, opposites attract. Consequently, eHarmony co je grindr is willing to facilitate only some types of legal marriage regardless of what the algorithm says. In terms of race however, the platform does allow customers to indicate their preference. Since the algorithm is not public, it is possible that eHarmony “puts a normative finger on the scale” to favor certain clients.

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