Reflections on Chapters 4 and 5 of Christian Rudder’s Dataclysm: Love, Sex, Race, and Identity–What Our Online Lives Tell Us about Our Offline Selves (‘You Gotta Be The Glue’ and ‘There’s No Success Like Failure’)
4.) A lot of big data analysis seems to me to be justifying the obvious. Teasing apart a massive set of information to capture and visualize the things we already know to be true. This might be the first step towards quantifying folk wisdom and making social science more scientific.
Of course, there are counter-intuitive surprises to be found in the process of discovery but this chapter doesn’t deal with any.
In this chapter, the author explores the point that couples who have more mutual friends are more likely to stay together. He shows how robust his relationship with his wife is by showing all the Facebook friends as a group of dot-and-line visualizations. All of their friends who are friends with each other are connected to each other by lines and so their unique friend groups are easily identifiable.
“Research using a variety of sources (e-mail, IM, telephone) has shown that the more mutual friends two people share, the stronger their relationship. More connections imply more time together, more common interests, and more stability.” He also examines what a couple whose social life isn’t so ’embedded’ would look like. Couples who aren’t each other’s most embedded node on their social network are 50% more likely to break up.
For me, the most interesting part of this chapter is the brief primer on the origins of network analysis. In 1735, the Swiss mathematician Leonhard Euler simplified the seven bridges of Königsberg down to a visual abstraction of lines and dots to prove that you couldn’t possibly cross all seven by walking across each one only one time. Since then, “Euler’s concept of nodes and edges, which at first unraveled nothing more than a day’s walk, has since helped us understand disease and its vectors, trucks and their routes, genes and their bindings, and of course, people and their relationships. And in just the last few decades, network theory’s application to these last have exploded–because the networks themselves have exploded.”
5.) We are often led to believe something is more important that it is. Oftentimes, the choices available to us influence our decisions without our even being aware. This chapter explores that bias and what data shows is truly important to us as consumers, citizens, and in our relationships.
The examples begin in web design and end up in dating, with an examination of a well-worn quote from Steve Jobs: “But by far the biggest cause of frustration is that people don’t understand what they actually need. As Steve Jobs said, ‘People don’t know what they want until you show them.’ What he didn’t say is that showing them, especially in tech, means playing a game of Pin the Tail on the Donkey with several million people shouting advice.” OKCupid has tried hundreds of iterations of presenting information to its users, each version highlighting both different
Most closely referenced here are two different datasets from OKCupid that suggest physical attractiveness isn’t very important when out on a first date with a stranger. The thing is, looks are heavily selected for because that’s about all the users have to go off of online. Other things people tend to say are very important don’t match user behavior. For example, caring about politics seems to actually be more predictive for a two strangers getting along than matching party affiliations.
As one of the architects of OKCupid’s choice architecture, this makes the author pause to reflect that, “Dating sites are designed to give people the tools and the information to get whatever they want out of being single–casual sex, a few fun dates, a partner, a marriage…anything. Stuff like height, political views, photos, essays, all of it is right there, easily sortable, easily searchable. It’s there to help people make judgments and fulfill their desires, and as fascinating as those judgments and desires may be to pic apart, there’s a side of it that I think does love a disservice. People make choices from the information we provide because we can, not because they necessarily should.”