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Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are by [Seth Stephens-Davidowitz]
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Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are Kindle Edition

4.4 out of 5 stars 1,606 ratings

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“This book is about a whole new way of studying the mind . . . an unprecedented peek into people’s psyches . . . Time and again my preconceptions about my country and my species were turned upside-down by Stephens-Davidowitz’s discoveries . . . endlessly fascinating.” -- Steven Pinker, author of The Better Angels of Our Nature

“A whirlwind tour of the modern human psyche using search data as its guide. . . . The empirical findings in Everybody Lies are so intriguing that the book would be a page-turner even if it were structured as a mere laundry list.” -- The Economist

“Move over Freakonomics. Move over Moneyball. This brilliant book is the best demonstration yet of how big data plus cleverness can illuminate and then move the world. Read it and you’ll see life in a new way.” -- Lawrence Summers, President Emeritus and Charles W. Eliot University Professor of Harvard University

Freakonomics on steroids―this book shows how big data can give us surprising new answers to important and interesting questions. Seth Stephens-Davidowitz brings data analysis alive in a crisp, witty manner, providing a terrific introduction to how big data is shaping social science.” -- Raj Chetty, Professor of Economics at Stanford University

“A tour de force―a well-written and entertaining journey through big data that, along the way, happens to put forward an important new perspective on human behavior itself. If you want to understand what’s going on in the world, or even with your friends, this is one book you should read cover to cover.” -- Peter Orszag, Managing Director, Lazard and former Director of the Office of Management and Budget

Everybody Lies is an astoundingly clever and mischievous exploration of what big data tells us about everyday life.  Seth Stephens-Davidowitz is as good a data storyteller as I have ever met.” -- Steven Levitt, co-author, Freakonomics

“Brimming with intriguing anecdotes and counterintuitive facts, Stephens-Davidowitz does his level best to help usher in a new age of human understanding, one digital data point at a time.” -- Fortune, Best New Business Books

“Everybody Lies relies on big data to rip the veneer of what we like to think of as our civilized selves. A book that is fascinating, shocking, sometimes horrifying, but above all, revealing.” -- Tim Wu, author of The Attention Merchants

“Stephens-Davidowitz, a former data scientist at Google, has spent the last four years poring over Internet search data . . . What he found is that Internet search data might be the Holy Grail when it comes to understanding the true nature of humanity.” -- New York Post

Everybody Lies is a spirited and enthralling examination of the data of our lives. Drawing on a wide variety of revelatory sources, Seth Stephens-Davidowitz will make you cringe, chuckle, and wince at the people you thought we were.” -- Christian Rudder, author of Dataclysm --This text refers to an alternate kindle_edition edition.

From the Inside Flap

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.

Everybody Lies combines the informed analysis of Nate Silver's The Signal and the Noise, the storytelling of Malcolm Gladwell's Outliers, and the wit and fun of Stephen Dubner and Steven Levitt's Freakonomics in a book that 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.

--Lawrence Summers, President Emeritus and Charles W. Eliot University Professor of Harvard University --This text refers to an alternate kindle_edition edition.

Product details

  • ASIN ‏ : ‎ B01AFXZ2F4
  • Publisher ‏ : ‎ Dey Street Books; Reprint edition (May 9 2017)
  • Language ‏ : ‎ English
  • File size ‏ : ‎ 7043 KB
  • Text-to-Speech ‏ : ‎ Enabled
  • Screen Reader ‏ : ‎ Supported
  • Enhanced typesetting ‏ : ‎ Enabled
  • X-Ray ‏ : ‎ Enabled
  • Word Wise ‏ : ‎ Enabled
  • Print length ‏ : ‎ 357 pages
  • Customer Reviews:
    4.4 out of 5 stars 1,606 ratings

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4.4 out of 5 stars
4.4 out of 5
1,606 global ratings
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Top reviews from Canada

Reviewed in Canada on August 29, 2018
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2.0 out of 5 stars An Accessible Treatment of an Important Subject - Warts and All
By Chillyfinger on August 29, 2018
The title turns out to refer to the "fact" that we lie all the time - a "fact" exposed by the author's study of Google queries that don't produce the same result as surveys. It's quite likely that both methods produce inaccurate results. The author is exposing discrepancies between methods, not "lies". The contrast is instructive. Traditional statistical analysis is rigorous but usually at the expense of making totally unreasonable assumptions about the relationship between what people "believe" and how people answer questionnaires. This is in contrast to "Big Data" which throws aside all pretext of mathematical rigor to seemingly peer into people's actual beliefs. Both methods are flawed for different reasons. When we discover a discrepancy, we are not discovering "lies".

Statistics has always been based on our efforts to use a large number of observations to estimate what is "going on" in a population. In practice, the assumptions of statistics rarely apply to the real world, as illustrated by the recent scandal about the validity (or lack thereof) of most published drug studies.

This book provides extensive insight into what amounts to an important modern advance in the field of statistics. The author provides valuable insight into how this effort can go wrong, not just in "big data" studies but in those involving ordinary logic. However, in spite of his obvious deep training in his field, he frequently forgets to define the "population" under study. What, for example, is the "population" of people who enter a Google query about their daughter's weight? Without a firm definition, all the truthy statistics are meaningless, as are comparisons (to three decimal precision) of one truthy statistic to another.

Overall, the field of Big Data, along with its stepsister, Deep Learning, generally abandons the already shaky rigor of statistics in favor of a "black box" that produces the desired truthy results. Sometimes the black box seems to get the right answer, sometimes not. Throw out the results that seem wrong (don't mention them). Keep the results that seem right. Don't mention the fact that we don't know how the box works.

A good companion to this book would be https://www.amazon.ca/Weapons-Math-Destruction-Increases-Inequality-ebook/dp/B019B6VCLO/ref=sr_1_1?s=digital-text&ie=UTF8&qid=1535565922&sr=1-1&keywords=weapons+of+math+destruction
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6 people found this helpful
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Reviewed in Canada on August 11, 2017
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Reviewed in Canada on August 8, 2018
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Reviewed in Canada on August 19, 2018
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Reviewed in Canada on November 29, 2020
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Top reviews from other countries

JWH
5.0 out of 5 stars Or "Everyone Tells The Truth to Google": A Fascinating Tour of the Big Data of the Internet
Reviewed in the United Kingdom on March 14, 2018
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10 people found this helpful
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The Cognologist
5.0 out of 5 stars Woohoo, what a read!
Reviewed in the United Kingdom on June 11, 2017
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15 people found this helpful
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GeordieReader
5.0 out of 5 stars Fascinating insight into what we can learn from big data
Reviewed in the United Kingdom on October 19, 2017
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9 people found this helpful
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Customer
4.0 out of 5 stars Good Read with some limited insights
Reviewed in the United Kingdom on November 18, 2017
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6 people found this helpful
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John G
3.0 out of 5 stars Big Data uses and abuses yes but..
Reviewed in the United Kingdom on August 30, 2018
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