Dataclysm

Who We Are (When We Think No One's Looking)

By: Christian Rudder

Narrated by: Kaleo Griffith

A New York Times Bestseller

An audacious, irreverent investigation of human behavior—and a first look at a revolution in the making

Our personal data has been used to spy on us, hire and fire us, and sell us stuff we don’t need. In Dataclysm, Christian Rudder uses it to show us who we truly are.

For centuries, we’ve relied on polling or small-scale lab experiments to study human behavior. Today, a new approach is possible. As we live more of our lives online, researchers can finally observe us directly, in vast numbers, and without filters. Data scientists have become the new demographers.

In this daring and original book, Rudder explains how Facebook "likes" can predict, with surprising accuracy, a person’s sexual orientation and even intelligence; how attractive women receive exponentially more interview requests; and why you must have haters to be hot. He charts the rise and fall of America’s most reviled word through Google Search and examines the new dynamics of collaborative rage on Twitter. He shows how people express themselves, both privately and publicly. What is the least Asian thing you can say? Do people bathe more in Vermont or New Jersey? What do black women think about Simon & Garfunkel? (Hint: they don’t think about Simon & Garfunkel.) Rudder also traces human migration over time, showing how groups of people move from certain small towns to the same big cities across the globe. And he grapples with the challenge of maintaining privacy in a world where these explorations are possible.

Visually arresting and full of wit and insight, Dataclysm is a new way of seeing ourselves—a brilliant alchemy, in which math is made human and numbers become the narrative of our time.

For my personal research

Very enlightening!!! I wasn’t aware of how our data is used and how it’s collected. Also the shocking truths backed by the data of how men and women choose potential partners is invaluable.

Too little data, too much pedantry

This book is a moderately well-written explainer of very standard left-wing political and social opinion. I don’t criticize except that it billed itself as being based on data analysis. Beware, the title is a misnomer.

Know thyself

A fascinating, if unsettling, look at true human behavior as extrapolated from Internet data. The chapters dealing with racism are some of the most revealing about American race relations.

Listen on 2X so you don’t waste as much time on this one.

Christian Rudder uses the data gleaned from the dating site he helped found (OK Cupid) to reinforce his own beliefs and biases.

Best book on big data yet!

There's a revolution going on around big data and this book explains it better than any other that I've read so far. The author explains how data is cataclysmic (like a flood), how it is changing the way we can study the world, and what are some of the kinds of conclusions we can draw about people by analyzing the data correctly.

Today is a social scientist's dream world. We can learn things about how individuals (or segmented groups) behave unlike any other time before in history and our abilities to understand our networks, desires and motivations are just waiting for some behavioral scientist (or even more nefariously an evil corporation or a corrupt government) to fully analyze the data trail we leave behind. Instead of guessing about human nature we are in a position to know about our behavior (at least for people up to the age of 50!, post 50 year olds aren't always fully represented in the datasets).

There is one warning about this book for audible listeners. Of all the books I have listened to this one handled tables and graphs the least effectively. Note to author: take a minute or two and re-write the graphs and tables with the audio version in mind. Sometimes the narrative got lost in reading a table out loud. I could follow the conversation, but it got deadly boring at times.

This book reminds me of a Gladwell book or Freakenomics, but is much better because it never strays from the data and never lets the model under discussion stray to far from what the data (reality) is really saying. The real strength of this book is not so much the specific examples he gives in the book, but it acts as a guide to how a smart person can change the data from just a bunch of messy information, to organized data, then to knowledge and then finally wisdom.