Secrets to Maximizing Success in the (Speed) Dating Experience
By: Ucla Datares
Tags: Data Visualization, Data, Datares, Dating Advice, UCLA

Secrets to Maximizing Success in the (Speed) Dating Experience

By Aaron Lee, Aden Chiu, Charlotte Huang, Grace Panos, Michelle Lee, and Teresa Rexin

Introduction

Now more than ever, the prospect of instant gratification has taken a hold of the dating world. Dating apps like Tinder and Bumble have capitalized on this phenomenon by allowing users to select potential matches based on appearance and single-sentence bios. Speed dating events have been going on for decades and are based on the idea that compatibility is pre-determined by certain attributes. Our group decided to analyze a speed dating dataset from Kaggle in order to make a conclusion about what factors generate attraction and influence “matches” between pairs of people. We hope you “super like” our interpretations!

Top Secret(s)

From our analysis, we were able to make the following conclusions about success in the (speed) dating experience:

Race doesn’t matter much in finding a match but age and career do. Males and females look for different qualities in their partners. Participants that perceive themselves as more attractive, fun, and ambitious tend to get more matches, possibly due to self-confidence in their own attributes. First and last impressions are important. Keep an open mind when going into any dating experience and have fun!

Speed Data-ing

Dataset Overview

This Speed Dating dataset was compiled by Columbia Business School professors Ray Fisman and Sheena Iyengar, originally used for their paper “Gender Differences in Mate Selection: Evidence From a Speed Dating Experiment.” Over 500 people ages 18–55 participated in the experimental speed dating events from 2002–2004. During the events, attendees had a four minute “first date” with participants of the opposite sex. After each date, participants rated their date on six attributes: Attractiveness, Sincerity, Intelligence, Fun, Ambition, and Shared Interests and whether they expected to match with their partner. The dataset also includes other questionnaire data about the participants including: demographics, dating habits, self-perception across key attributes, beliefs on what others find valuable in a mate, and lifestyle information.

It’s important to acknowledge that the data is from 2002–2004 — nearly twenty years ago. These findings may have been reflective of different cultural values and preferences at the time. When looking at the distribution of ages, it is evident that most participants were under thirty years of age. Therefore, our findings are more applicable to younger people, and we can not necessarily consider them reflective of people of all ages looking for a partner.

Data Cleaning Process

Many of the variables in the dataset did not have an intuitive naming structure, so we examined the Speed Dating Data Key provided with the dataset and read excerpts from the paper to understand the methodology of the data collection. Then, we determined which factors we wanted to examine (such as race, career, and various ranking of attributes) and removed redundant columns in the dataset (such as “field” which measures the same information as “career”). Due to the nature of the experiment, some of the recorded attributes had rows of missing data since some attributes were only recorded for certain groups of people. Thus, we removed these columns with sparse data.

Another aspect of data cleaning was normalizing the attribute rankings. Some groups were told to rank the attributes out of 10 independent of one another, while other groups were given a total of 100 points to be distributed among the five attributes. We decided to normalize the data by converting the scores out of 10 to be out of 100. We accomplished this by summing the attribute scores for each participant, finding the proportion of each of the attributes, then multiplying this by 100.

(S)he’s All That

First, we investigated general characteristics including race, age, and career to determine what matters to participants in a speed dating experience.

Race

We found that race is not a defining factor in terms of speed dating choices. Based on the data, the match rate for participants whose partners were the same race was 17.07%, and those of different races was 16.08% — this is only a 1% difference. But of the five race categories studied: African-American, Caucasian, Latino, and Asian (everyone else listed as other), there were differences in races getting a match.

African-Americans had the highest match percentage with a 20% chance of matching. Asians had the lowest match percentage with only 13%. However, more information may be required to see whether these results apply to long-term relationships as opposed to speed-dating.

Age

In addition to race, we looked into another demographic factor: age. The total number of matches for both females and males follow an approximately normal curve. The total number of matches for females was highest at age 27, while total matches were highest for males at age 25. We compiled this with the match rate (proportion of matches a participant would get) among each gender and age.