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review 2017-09-15 22:01
Dataclysm by Christian Rudder
By Christian Rudder Dataclysm: Who We Are (When We Think No One's Looking) - Christian Rudder

On its face this book sounds good: data guru uses the information people share online, particularly on the dating website OkCupid, to reveal demographic trends. There is some interesting information here, along with fun graphs and charts. But while Rudder may be a good statistician, he’s a poor sociologist, and the book is riddled with eyebrow-raising assumptions and conclusions. It also hangs together poorly, jumping from one disconnected subject to another, with chapters that share a fairly simple finding padded by repetitive discussions of the author’s methods and rhapsodizing about the scope of his data. For a better book on what Big Data says about us, I recommend the more recent Everybody Lies.

Unfortunately, Rudder begins the book with random, skewed guessing. In describing OkCupid, he confidently asserts that “[t]onight, some thirty thousand couples will have their first date because of OkCupid. Roughly three thousand of them will end up together long-term. Two hundred of those will get married[.]” This caught my attention immediately: 10% of online first dates leading to long-term relationships is a fantastic success rate, but less than 7% of long-term relationships ending in marriage seems awfully low for the 20’s-and-up crowd. Curious what definition of “long-term” Rudder was using, I flipped to the notes at the back, only to find that he made it all up based on the fact that the site has 4 million active users and 300 couples per day reporting that they are leaving OkCupid because they found someone on the site. Plus his intuition that fewer than 1 in 10 long-term couples get married: “How many serious relationships did you have before you found the person you settled down with? I imagine the average number is roughly 10.” My own experience of the world is very different (I don’t think I know anyone who’s had 10+ long-term, serious relationships). And since the average American woman marries at 27 and man at 29, and according to the CDC, the average adult woman reports 4 lifetime sexual partners while the average man reports 6-7, Rudder’s impression seems the more likely to be skewed.

The author’s conclusions are equally questionable. He observes that men seem to find 20-year-old women the most attractive (at least on a site evidently without teenagers) throughout their lives, while women’s view of male attractiveness changes to accommodate their own age, and concludes that middle-aged men don’t contact young women for fear of rejection and social judgment. This overlooks the fact that there’s much more to a relationship than physical attractiveness; how many 50-year-old men want to live in a world of exam stress and frat parties, with a partner who has comparatively little life experience?

Another chapter seems to confuse correlation and causation. In “You’ve Gotta be the Glue,” Rudder explains that couples who each have multiple clusters of Facebook connections from different areas of their lives, and are the only person connected to each other’s various tribes, last longer than couples who are connected to all the same people, who all know each other. This makes sense: if you belong to several social groups (co-workers, college friends, book club, etc.) and your partner has gotten to know all of them, your relationship is well-established and likely serious. But if you belong to a tight-knit community and start dating someone within your group, your Facebook connections provide no indication of how serious you are. Rudder, however, interprets the data as proving causation, concluding that the “specialness” of the couple in being the “glue” between different social groups somehow boosts the relationship. He fails to explain how “connecting” his gaming buddies to his wife’s extended family strengthens their marriage – presumably if these social groups cared to mingle much, they’d befriend each other on Facebook and then what happens to the couple’s “specialness”?

When the book moves away from dating-related data, it becomes a series of disconnected one-off chapters. There’s a discourse about group rage on the Internet that involves little data analysis and seems to be included because the author is interested in group rage on the Internet. There’s a chapter about the language used in Twitter posts, concluding that Twitter definitely isn’t killing sophisticated thought because “a,” “and,” and “the” are among the top 10 words used in English both on Twitter and off of it. There’s an equation meant to demonstrate that multiplying a word’s frequency rank in a text by its number of uses will result in a constant, but the chart meant to illustrate this point with Ulysses displays a “constant” ranging from 20,000 to 29,055.

All that said, there is some interesting material here, particularly the data on race. The chapter on racist Google searches is less relevant now that the author of that study has written his own book (the aforementioned Everybody Lies); and Dataclysm, published in 2014, has a rosier view of this than the 2017, Trump-era version. But the study showing massive racial differences in how people rate one another’s attractiveness is still quite relevant: key findings include the fact that people tend to view members of their own race as more attractive than others, but black Americans take a major hit in the ratings from everybody (including other black people, though to a lesser degree). My first reaction on reading this was that it’s hard to judge people for preferring cultural commonalities in their most intimate relationships. But the data isn’t so simple: it’s based on how people rate a photo, not whom they choose to contact, and attractiveness doesn’t only affect one’s dating prospects, but employment too (there’s a chart on that). And in-group biases in American society are hardly limited to dating; while our neighborhoods, schools, workplaces, churches, and friend groups are still largely separate, I’m inclined to believe that Rudder’s data does show hidden bias.

Overall, while there are interesting nuggets in here, I wouldn’t recommend the book. A few interesting data points are padded into book-length by ill-conceived interpretations and rambling. By the end I was simply tired of it – the writing didn’t engage me when unaccompanied by charts, the book lacks cohesion and the author had lost far too much credibility. Try Everybody Lies instead.

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text 2014-10-28 04:58
Perfect Gift for Annoying Uncles
By Christian Rudder Dataclysm: Who We Are (When We Think No One's Looking) - Christian Rudder

Do you have one of those uncles who makes the holidays suck by offering his (it's almost always a guy, sadly) political opinions unasked? Give him this book. Seriously, if I could force all the political blowhards, the Rush Limbaugh, Rachel Maddow, and Bill O'Reilly types, to read just one book--this would be it.


Want to know if racism is over because we elected a black president? See the answer in cold hard numbers here. (Spoiler alert: It's not.) Rudder, from his unique position at OKCupid, lays bare America's soul using big data. Some of his findings are encouraging--particularly the steady decline in homophobia. Other findings are downright depressing--the data on sexism and its connection with female attractiveness, for example. All of Rudder's findings are interesting. I devoured this book in two days, and found myself wishing I'd bought it instead of checking it out from the library, a mistake I'll probably correct when it comes out in paperback. 


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review 2014-09-09 15:22
By Christian Rudder Dataclysm: Who We Are (When We Think No One's Looking) - Christian Rudder

If you are a Twitter user, congratulate yourself: your average word length is greater than Shakespeare’s. If you are a man or a woman, I know what age group you find most attractive. I also know those naughty and bizarre things you search for in Google.


Okay, I fess up. I don’t know YOU, but I know the collective representation of you thanks to Christian Rudder’s new book DATACLYSM. And, dang it…I know a bit more about myself, too.


Rudder got me interested in his book when he started talking about the dating site he co-founded, OKCupid. So much data! I loved peeking in with him as he explored what happened when photos were removed from the site and people went on blind dates (hint: ugly folks make great dates). Then later when the pictures were made larger (hint: beautiful people received tons more messages; homely folks even fewer than before). Everything was extrapolated, even down to the average keystrokes versus average message length of messages (can you figure out how 1,000 letters are typed just by pressing 10 keys?).


Rudder kept his Harvard math powers rolling through Twitter, Craigslist, Google, and—my favorite—reddit. WARNING: I spent way too many hours last night rolling through Google trends. Be prepared. You will lose precious time fondling the data in this book.


One more thing: Rudder is hilarious and insightful. Describing what we learn from Google, he writes, “It’s the site acting not as Big Brother but as older Brother, giving you mental cigarettes”. Going back to Twitter versus Shakespeare (average word length 4.8 versus 3.99, respectively), Rudder writes, “Looking through the data, instead of a wasteland of cut stumps, we find a forest of bonsai.” As for the data on his OkCupid site, he writes, “People saying one thing and doing another is pretty much par for the course in social science.”


The one thing I can complain about is the length of the book: I want more! At 300 pages, I would say about 100 of those pages are devoted to end-of-book references and section-introduction pages. The good news is that Rudder has his blog with tons more data, and the book has its own site, too. The book’s site is supposed to have several tools on it, such as an algorithm to predict if you are going to divorce or break-up based on your Facebook profile. Those features were not available before the book’s publication.


Bottom line: tons of data and insight provided through creative charting and exquisite writing. I love it.


Thanks to Crown for sending this to me for review. Pure awesome!



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review 2014-09-01 11:17
Dataclysm by Christian Rudder
By Christian Rudder Dataclysm: Who We Are (When We Think No One's Looking) - Christian Rudder

“I’m taking something big - an enormous set of what people are doing and thinking and saying, terabytes of data - and filtering from it many small things: what your network of friend says about the stability of your marriage, how Asians (and whites and blacks and Latinos) are least likely to describe themselves, where and why gay people stay in the closet, how writing has changed in the last ten years, and how anger hasn’t. The idea is to move our understanding of ourselves away from narratives and toward numbers, or, rather, thinking in such a way that numbers are the narrative.”

Dataclysm takes the recent phenomenon of metadata and mass surveillance and attempts to present a different side of it: it can be used to control people, but it can also open up unprecedented opportunities for research, history and understanding human nature.

The author, Christian Rudder, is a mathematics major and one of the co-founders of online dating site OkCupid. He decided to take the massive amounts of data they’ve amassed over the years at his website and try to make some sense out of it. In his quest to understand humanity (or at least the part of it that’s online, and mainly in the US) he also enlists the data collected and made available by other companies, including Google and Twitter.

His style of writing is conversational and unflinchingly honest (the chapter at the end, where he writes about the fallacies and shortcomings of data and research, should be included in every non-fiction book out there). He tackles topics that are usually deemed too sensitive for people to talk about, including hidden attitudes towards race, gender and sexual preferences. He also seems to have a balanced view of the possibilites of metadata - the good, the bad and the ugly - for someone who makes his living off it. He does try to paint an overall positive picture, but doesn’t gloss over the negative consequences (for example, at one point, he says that big data is very good, specially for companies and institutions, not so much for the common person), which keeps the book from turning into a preachy “big data is great!” manifesto. 

(As far as I’m concerned, I disagree with his view that the positives outweigh the negatives.)

The themes are a little all over the place, as if he wasn’t quite sure what he wanted the book to be about and just picked the findings that would be more popular, with a strong emphasis on romance (which is not surprising, given the author’s line of work). But it never seems over-stretched, as is often the case with non-fiction books.

Recommended if you’re at all interested in big data, surveillance, psychology and pop science. 


Note: I got this book for review purposes through NetGalley.

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