Big Data, New Data, and What the Internet Can Tell Us About Who We Really AreBook - 2017 | First edition.
"How much sex are people really having? How many Americans are actually racist? Is America experiencing a hidden back-alley abortion crisis? Can you game the stock market? Does violent entertainment increase the rate of violent crime? Do parents treat sons differently from daughters? How many people actually read the books they buy? In this groundbreaking work, Seth Stephens-Davidowitz, a Harvard-trained economist, former Google data scientist, and New York Times writer, argues that much of what we thought about people has been dead wrong. The reason? People lie, to friends, lovers, doctors, surveys--and themselves. However, we no longer need to rely on what people tell us. New data from the internet--the traces of information that billions of people leave on Google, social media, dating, and even pornography sites--finally reveals the truth. By analyzing this digital goldmine, we can now learn what people really think, what they really want, and what they really do. Sometimes the new data will make you laugh out loud. Sometimes the new data will shock you. Sometimes the new data will deeply disturb you. But, always, this new data will make you think. [This] book will change the way you view the world. There is almost no limit to what can be learned about human nature from Big Data--provided, that is, you ask the right questions."
From the critics
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"At the risk of sounding grandiose, I have come to believe that the new data increasingly available in our digital age will radically expand our understanding of humankind. The microscope showed us there is more to a drop of pond water than we think we see. The telescope showed us there is more to the night sky than we think we see. And new, digital data now shows us there is more to human society than we think we see. It may be our era's microscope or telescope—making possible important, even revolutionary insights."
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Big data has been much hyped as the next big thing in science, but Everybody Lies sets out to show what can be done with big data that wasn’t possible before, while also acknowledging its shortcomings, and the ways it can be complemented by traditional small data collection techniques. Seth Stephens-Davidowitz makes the argument that the Google dataset he has been working with is particularly valuable, because unlike even anonymous surveys, users have an incentive to be honest, and little or no sense of wanting to impress anyone. To get the information they want from Google, they must query honestly about even the most taboo subjects, from sex to race to medical problems. Facebook, for example, is not nearly as useful, because people are consciously presenting a certain version of themselves to their friends. But if you want Google to bring you back the “best racist jokes,” you have to tell it so. You can’t hide, and still get what you want. The result is a partial but unprecedented glimpse into the human mind.
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