The computer-dating pioneers were happy to play up to the image of the omniscient machine — and were already wary of any potential stigma attached to their businesses. We supply everything but the spark.
Love and dating after the Tinder revolution - BBC News
DeWan made the additional claim that Contact's questions were more sophisticated than Match's nationwide efforts, because they were restricted to elite college students. In essence, it was the first niche computer-dating service. Over the years since Tarr first starting sending out his questionnaires, computer dating has evolved. Most importantly, it has become online dating. And with each of these developments — through the internet, home computing, broadband, smartphones, and location services — the turbulent business and the occasionally dubious science of computer-aided matching has evolved too.
Online dating continues to hold up a mirror not only to the mores of society, which it both reflects, and shapes, but to our attitudes to technology itself. The American National Academy of Sciences reported in that more than a third of people who married in the US between and met their partner online, and half of those met on dating sites. The rest met through chatrooms, online games, and elsewhere. Preliminary studies also showed that people who met online were slightly less likely to divorce and claimed to be happier in their marriages.
The latest figures from online analytics company Comscore show that the UK is not far behind, with 5.
The algorithm method: how internet dating became everyone's route to a perfect love match
When online dating moves not only beyond stigma, but beyond the so-called "digital divide" to embrace older web users, it might be said to have truly arrived. It has taken a while to get there. It believed it could do this thanks to the research of its founder, Neil Clark Warren, a then old psychologist and divinity lecturer from rural Iowa.
His three years of research on 5, married couples laid the basis for a truly algorithmic approach to matching: Whatever you may think of eHarmony's approach — and many contest whether it is scientifically possible to generalise from married people's experiences to the behaviour of single people — they are very serious about it. Since launch, they have surveyed another 50, couples worldwide, according to the current vice-president of matching, Steve Carter. When they launched in the UK, they partnered with Oxford University to research 1, British couples "to identify any cultural distinctions between the two markets that should be represented by the compatibility algorithms".
And when challenged by lawsuits for refusing to match gay and lesbian people, assumed by many to be a result of Warren's conservative Christian views his books were previously published in partnership with the conservative pressure group, Focus on the Family , they protested that it wasn't morality, but mathematics: As part of a settlement in one such lawsuit, eHarmony launched Compatible Partners in These services rely on the user supplying not only explicit information about what they are looking for, but a host of assumed and implicit information as well, based on their morals, values, and actions.
What underlies them is a growing reliance not on stated preferences — for example, eHarmony's question surveys result in a detailed profile entitled "The Book of You" — but on actual behaviour; not what people say, but what they do. Despite competition from teams composed of researchers from telecoms giants and top maths departments, Potter was consistently in the top 10 of the leaderboard. A retired management consultant with a degree in psychology, Potter believed he could predict more about viewers' tastes from past behaviour than from the contents of the movies they liked, and his maths worked.
He was contacted by Nick Tsinonis, the founder of a small UK dating site called yesnomayb, who asked him to see if his approach, called collaborative filtering, would work on people as well as films. Collaborative filtering works by collecting the preferences of many people, and grouping them into sets of similar users.
Because there's so much data, and so many people, what exactly the thing is that these groups might have in common isn't always clear to anyone but the algorithm, but it works. The approach was so successful that Tsinonis and Potter created a new company, RecSys , which now supplies some 10 million recommendations a day to thousands of sites. RecSys adjusts its algorithm for the different requirements of each site — what Potter calls the "business rules" — so for a site such as Lovestruck.
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Likewise, while British firm Global Personals provides the infrastructure for some 12, niche sites around the world, letting anyone set up and run their own dating website aimed at anyone from redheads to petrolheads, all 30 million of their users are being matched by RecSys. Potter says that while they started with dating "the technology works for almost anything". RecSys is already powering the recommendations for art discovery site ArtFinder, the similar articles search on research database Nature.
Of particular interest to the company is a recommendation system for mental health advice site Big White Wall. Because its users come to the site looking for emotional help, but may well be unsure what exactly it is they are looking for, RecSys might be able to unearth patterns of behaviour new to both patients and doctors, just as it reveals the unspoken and possibly even unconscious proclivities of daters. Back in Harvard in , Jeff Tarr dreamed of a future version of his Operation Match programme which would operate in real time and real space. He envisioned installing hundreds of typewriters all over campus, each one linked to a central "mother computer".
Anyone typing their requirements into such a device would receive "in seconds" the name of a compatible match who was also free that night. Recently, Tarr's vision has started to become a reality with a new generation of dating services, driven by the smartphone.
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Suddenly, we don't need the smart algorithms any more, we just want to know who is nearby. But even these new services sit atop a mountain of data; less like Facebook, and a lot more like Google. Tinder, founded in Los Angeles in , is the fastest-growing dating app on mobile phones but its founders don't like calling it that.
According to co-founder and chief marketing officer Justin Mateen, Tinder is "not an online dating app, it's a social network and discovery tool". He also believes that Tinder's core mechanic, where users swipe through Facebook snapshots of potential matches in the traditional "Hot or Not" format, is not simple, but more sophisticated: Online dating is going mainstream. The study is based on a survey of 2, U. Young adults are leading the surge in online dating, with usage among to year-olds almost tripling since Pew's online dating study.
Call it the Tinder factor: Aaron Smith, author of the report, told NPR that mobile apps' appeal lies in their simplicity and " game-ified way of engaging with other people. Online dating is a big market. Here in the U.go here
Love and dating after the Tinder revolution
Match, whose portfolio includes OkCupid, Tinder and Match. Investors are interested in the market's potential: Still, despite the increasing popularity of online dating, concerns remain over the industry's ability to generate a profit. The biggest issue is that, when the apps work and people find partners, they stop using the service. As a result, dating apps must be adept at acquiring new customers. Unfortunately, as the Wall Street Journal points out , most dating apps don't experience the same meteoric rise that Grindr and Tinder have, and users generally don't recommend the latest apps to their friends.
Match's first quarterly earnings illustrate the potential hurdles within the online dating industry. Following the earnings report, Barclays downgraded the stock, and both JPMorgan and Merrill Lynch lowered their price targets.
Keeping these challenges in mind as well as the industry's growth , let's take a look at what analysts expect to see from online dating companies when they next report earnings. Analysts provide estimates for various aspects of a company's operations, including its net income, earnings per share and revenue. The consensus estimate, which is the average of the provided figures, is then used as a benchmark come earnings season. If a company surpasses estimates, that's a positive earnings surprise and can boost a stock. On the other hand, missing estimates is a negative earnings surprise and can tank a stock.
Below is a list of online dating stocks and analyst estimates for their next quarterly earnings and revenue. Operates an online dating platform in the People's Republic of China.