Everybody Lies
Foreword by Steven Pinker, author of Thr Better Angels of our Nature Blending the informed analysis of The Signal and the Noise with the instructive iconoclasm of Think Like a Freak, a fascinating, illuminating, and witty look at what the vast amounts of information now instantly available to us reveals about ourselves and our world—provided we ask the right questions.By the end of an average day in the early twenty-first century, human beings searching the internet will amass eight trillion gigabytes of data. This staggering amount of information—unprecedented in history—can tell us a great deal about who we are—the fears, desires, and behaviors that drive us, and the conscious and unconscious decisions we make. From the profound to the mundane, we can gain astonishing knowledge about the human psyche that less than twenty years ago, seemed unfathomable.Everybody Lies offers fascinating, surprising, and sometimes laugh-out-loud insights into everything from economics to ethics to sports to race to sex, gender and more, all drawn from the world of big data. What percentage of white voters didn’t vote for Barack Obama because he’s black? Does where you go to school effect how successful you are in life? Do parents secretly favor boy children over girls? Do violent films affect the crime rate? Can you beat the stock market? How regularly do we lie about our sex lives and who’s more self-conscious about sex, men or women?Investigating these questions and a host of others, Seth Stephens-Davidowitz offers revelations that can help us understand ourselves and our lives better. Drawing on studies and experiments on how we really live and think, he demonstrates in fascinating and often funny ways the extent to which all the world is indeed a lab. With conclusions ranging from strange-but-true to thought-provoking to disturbing, he explores the power of this digital truth serum and its deeper potential—revealing biases deeply embedded within us, information we can use to change our culture, and the questions we’re afraid to ask that might be essential to our health—both emotional and physical. All of us are touched by big data everyday, and its influence is multiplying. Everybody Lies challenges us to think differently about how we see it and the world.

Everybody Lies Details

TitleEverybody Lies
Author
FormatHardcover
ReleaseMay 9th, 2017
PublisherDey Street Books
ISBN0062390856
ISBN-139780062390851
Number of pages354 pages
Rating
GenreNonfiction, Psychology, Science, Sociology, Technology

Everybody Lies Review

  • Will Byrnes
    May 2, 2017
    …people’s search for information is, in itself, information. When and where they search for facts, quotes, jokes, places, persons, things, or help, it turns out, can tell us a lot more about what they really think, really desire, really fear, and really do than anyone might have guessed. This is especially true since people sometimes don’t so much query Google as confide in it: “I hate my boss.” “I am drunk.” “My dad hit me.” There’s lies, damned lies and then there are statistics. One must won …people’s search for information is, in itself, information. When and where they search for facts, quotes, jokes, places, persons, things, or help, it turns out, can tell us a lot more about what they really think, really desire, really fear, and really do than anyone might have guessed. This is especially true since people sometimes don’t so much query Google as confide in it: “I hate my boss.” “I am drunk.” “My dad hit me.” There’s lies, damned lies and then there are statistics. One must wonder. Do the lies get bigger as the datasets grow? Seth Stephens-Davidowitz posits that the availability of vast sums of new data not only allows researchers to make better predictions, but offers them never-before-available tools that can offer insight that direct questioning never could. We have seen steps up of this type before. Malcolm Gladwell has made a career of such, with Blink, Outliers, and The Tipping Point. Freakonomics is the one I would expect most folks would know. Nate Silver put his data expertise into The Signal and the Noise. All these looks at data and how we interpret it rely on the analyst, regardless, pretty much, of the data. While the same might be true of Stephens-Davidowitz’s approach, he focuses on the availability of materials that have not been there in the past. The smarts that must be applied to get the most interesting results can now be applied to new oceans of data. It is more possible than it has ever been to draw inferences and actually test them out. In addition to the volume of data that is now available, there is the sort. The author looks at Google and FB data for evidence of underlying realities. Surveys can sometimes offer inaccurate outcomes, when the people being queried do not provide honest answers. Are you a racist? Yes/No. But one can look at what people enter into Google to get a sense of possible racism by geographic area. The everyday act of typing a word or phrase into a compact rectangular white box leaves a small trace of truth that, when multiplied by millions, eventually reveals profound realities. Looking for queries on jokes involving the N-Word, for example, turns out to yield a telling portrait of anti-black sentiment, which also correlates with lower black life expectancy. (And pro-Trump vote totals) We are treated to looks into a variety of research subjects, from picking the ponies, to seeing what really interests/concerns people sexually, looking for patterns of child abuse, selecting the best wine, using the texts of a vast number of books and movie scripts to come up with six simple plot structures.I thought the most interesting piece was on the use of associations, and provoking curiosity, rather than relying on overt statements to influence how people feel about a different group of people. Another was on using a data comparison of one’s (anonymous) medical information to others who share many characteristics to improve medical diagnoses.There are some areas in which it was not entirely persuasive that the methodology in question was tracking what was claimed. SS-D sees in searches of Pornhub, for example, what people really want and really do, not what they say they want and say they do. Really? I expect that what people check out on-line does not necessarily track with what might be of interest in real life. It would be like someone with an interest in mysteries being thought to have homicidal tendencies after searching for a variety of homicide related titles. Should a writer doing research into a dark subject like child pornography, human trafficking or cannibalism expect the heavy knock of the police on his/her door? Where is the line between an academic or titillation search and one made for planning?SS-D makes a point about there being a significant difference between searches that offer projections for groups or areas, and their inapplicability for predicting individual behavior, although that will not necessarily remain the case. In baseball, for example, the explosion of available information may very well be applied to specific players to diagnose and even correct flaws in technique, or recognize patterns that might expose underlying medical issues, or predict their arrival. The Big Data related here is much more macro, looking at group proclivities. Useful for spotting trends, measuring public sentiment, but in more detail than has been heretofore possible.And of course there is the impact of dark players. Those with the resources and motivation could manipulate the Big Data produced by Google and Facebook. Such players would not necessarily be limited to Russian cyber-spies and pranksters, but corporate and ideological players as well, like Robert Mercer. There could have been a bit more in here on those concerns.The book offers plenty of anecdotal bits that could have been lifted from any of the other data books noted at the top of this review. What one needs, ultimately is smart, insightful analysis. Having all the data in the world (that means you, NSA) is merely a burden unless there is someone insightful enough to figure out the right questions to ask, and how to ask them.SS-D notes several Google (Trends, Ngrams, Correlate) services that might be familiar to folks doing actual research, but which were news to me. It might be useful to check out some of these, maybe even come up with meaningful queries to shed light on pressing, or even completely frivolous questions.Not all problems can be solved, or even examined by the addition of ever more data. Sometimes, many times, the information that is available is perfectly appropriate to the task, but other factors prevent the joining together of its various pieces to create a meaningful whole. The now classic example is the from 9/11, when an absence of coordination between the CIA and FBI resulted in suicide bombers who could have been foiled succeeding in their mission. Politics and the culture of nations and organizations figure into how data is usedSo if everybody lies, is Seth Stephens-Davidowitz telling us the truth? I am sure there is a query one could construct that would look at diverse data sources, pull them all together and give us a fuller picture, but for now, we will have to make do with reading his book and articles, checking out his videos, applying the analytical tools already incorporated into our brains, and seeing if there is enough information there with which to come to a well-grounded conclusion. And that’s no lie.Review posted – May 5, 2017Publication date – May 9, 2017=============================EXTRA STUFFLinks to the author’s personal, Twitter, and FB pagesVIDEOS – SS-D speaking----- Stanford Seminar - Insights with New Data: Using Google Search Data-----Google Sex with Seth Stephens-Davidowitz - Arts & Ideas at the JCCSF----- Big Data and the Social Sciences - The Julis-Rabinowitz Center for Public Policy and Finance
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  • linhtalinhtinh
    May 11, 2017
    A pretty short book with some interesting remarks, but not yet charming enough for me. The author definitely has his quirky and funny moments, when he presents himself, his family, and especially his views more. Yet the books' ideas and findings aren't exactly ground breaking. The types of questions like this have been posed in Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. The usefullness of big data has been discussed by ones such as Dataclysm: Who We Are (discussion o A pretty short book with some interesting remarks, but not yet charming enough for me. The author definitely has his quirky and funny moments, when he presents himself, his family, and especially his views more. Yet the books' ideas and findings aren't exactly ground breaking. The types of questions like this have been posed in Freakonomics: A Rogue Economist Explores the Hidden Side of Everything. The usefullness of big data has been discussed by ones such as Dataclysm: Who We Are (discussion on sex and gender actually resemble Dataclysm a lot). I was looking for something more nuanced, a long and rigorous thematic research on human's tendency, and data as an extremely useful tool but not the main focus. Instead, it's more like a collection of observations. Each time Stephens-Davidowitz has an idea, he looks for answer from the available data, then moves on. The questions are somewhat related to human's private behaviors that traditionally we can't observe. The tool seems to be a bit more at the center here, but he doesn't discusses the cons and all the ethical implications of big data that deep enough, except for a short section at the end of the book. Now, that's totally ok, for a casual and light, yet still useful read. More importantly, we have to consider that these type of research and the topic of big data are still relatively new. It takes decades and decades more to build a literature huge enough to draw really meaningful and profound conclusions. The time simply hasn't arrived yet for the book of my taste, but this one, as the author states, hopefully would raise interests in young people, young social scientist, steering them towards potentially fruitful topics and research methodologies. That's why it's a 3 star.
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  • Lolly K Dandeneau
    April 25, 2017
    via my blog: https://bookstalkerblog.wordpress.com/“In 2014, there were about 6,000 searches for the exact phrase “how to kill your girlfriend” and 400 murders of girlfriends.” As a chapter tells us, ALL THE WORLD’S A LAB. The data collected and shared by Seth Stephens- Davidowitz is downright disturbing at times. That there are dark sexual proclivities isn’t shocking so much as what they are, based on research. Also, who knew that your neighbor winning the lottery can have a strange impact on y via my blog: https://bookstalkerblog.wordpress.com/“In 2014, there were about 6,000 searches for the exact phrase “how to kill your girlfriend” and 400 murders of girlfriends.” As a chapter tells us, ALL THE WORLD’S A LAB. The data collected and shared by Seth Stephens- Davidowitz is downright disturbing at times. That there are dark sexual proclivities isn’t shocking so much as what they are, based on research. Also, who knew that your neighbor winning the lottery can have a strange impact on your own life. How odd human nature, what bizarre subjects human beings become, and subjects of research, it seems, we all are. What the heck does google searches reveal about us? A lot, actually. I spent a few chapters of this book with my moth hanging open, catching flies. Ethical questions certainly give rise to much of the research, just where is the ‘internet’ taking us all? Just who is watching, why? Well, read on my fellow test subjects. Do we think in strange ways? Naturally. I struggle with the methods of collecting data and yet, it’s true that while it can be used for nefarious purposes, just like anything else, there can be great benefits too.How can we know what is real? How can anyone trust searches as solid fact? Data makes some of us cross eyed with boredom, but here Seth Stephens-Davidowitz presents it in a manner most people can understand and also be humored and at times shocked by. I will never think about strawberry pop tarts without thinking about hurricanes. A strange comment, but that’s what this book is all about- the bizarre data we provide, whether we realize it or not. Are we really just a bunch of liars? Do we all just masquerade online? Is the world so twisted? Just how much can you really measure to determine the future of what’s hot, what will sell, what stocks will rise and fall? How did one man predict the success of the horse American Pharoah? Who gives corporations the right to use collected data, and should they?How do interests and fun tests measure IQ on facebook? Just what is our doppelganger and why does it matter? And hilariously, how many of the readers finish books? What about this one? Well, I did. I particularly enjoyed the chapter “Was Freud Right?” I wonder, were he alive today, how much of his theories would stand up to actual research. The Banana dream data is food for thought and yes I’m trying to be punny here, I wonder what that means about me, according to research.The information isn’t overbearing, and most of it is fascinating. Statistically, you may well finish this book too.Publication Date: May 9, 2017Dey Street Books
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  • Peter Mcloughlin
    May 25, 2017
    This book looks into the things we reveal about ourselves that no one can see except Google. Big Data overturns rocks and reveals some creepy crawlies in our body politic lurking on the underside of our public face. Be it very revealing searches on Pornhub to people looking for racist jokes on their search engines some ugly things are happening with people when no one is looking but your (hopefully anonymous) web browser. Aggregate data reveals our kinks some of which are quite dark and people's This book looks into the things we reveal about ourselves that no one can see except Google. Big Data overturns rocks and reveals some creepy crawlies in our body politic lurking on the underside of our public face. Be it very revealing searches on Pornhub to people looking for racist jokes on their search engines some ugly things are happening with people when no one is looking but your (hopefully anonymous) web browser. Aggregate data reveals our kinks some of which are quite dark and people's racism which is even darker. Big data has the ability to turn soft social sciences into something much more firm. Hand waving goes out the window when good data takes hold. This book might be worth a look because the things that are being revealed will soon loom larger as big data gets more refined in its techniques.
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  • Jessica
    April 26, 2017
    This book tries too hard to be Freakonomics. The first two parts are full of random examples of interesting but mostly pointless things that can learned via Google search trends. However, a whole lot of assumptions are made off these bits of data that don't seem to have much basis in factual scientific methods of research. Unprofessional jokes are thrown in randomly. If you need a footnote to explain why a joke was not homophobic maybe you should have just skipped the joke. And any book of less This book tries too hard to be Freakonomics. The first two parts are full of random examples of interesting but mostly pointless things that can learned via Google search trends. However, a whole lot of assumptions are made off these bits of data that don't seem to have much basis in factual scientific methods of research. Unprofessional jokes are thrown in randomly. If you need a footnote to explain why a joke was not homophobic maybe you should have just skipped the joke. And any book of less than 300 pages of text should not need to use the same example three times, especially when it's about how the author can't believe women are concerned about the smell of their vagina.The last section of the book explains the limitations big data holds and is really the most grounded section, the rest being almost hagiography. It would have done a lot to work the third section into the examples of the first two sections. It would have balanced out the praise and also would have done much to explain the flaws present in some of the examples included.Some cool facts buried in a lot of murky oddness.Disclaimer: I was given this book in a Goodreads giveaway.
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  • Jason Park
    April 14, 2017
    I received an ARC of this book as a giveaway from Goodreads, but my opinions are my own.I wasn't sure what to think of this book when I started it. I had never heard of Seth Stephens-Davidowitz or the publisher before, but it seemed like it could be a thought-provoking book and a learning experience. I was right, but I also had a few problems.Positives first. Like I said, I was skeptical from the beginning. I even actively disliked it at one point (see below). But then I reached Chapter 3, where I received an ARC of this book as a giveaway from Goodreads, but my opinions are my own.I wasn't sure what to think of this book when I started it. I had never heard of Seth Stephens-Davidowitz or the publisher before, but it seemed like it could be a thought-provoking book and a learning experience. I was right, but I also had a few problems.Positives first. Like I said, I was skeptical from the beginning. I even actively disliked it at one point (see below). But then I reached Chapter 3, where he went full Malcolm Gladwell with a story about American Pharoah. This and some later, similar sections were the highlights of the book, and it generally won me over. Stephens-Davidowitz is a talented researcher and has the potential to write about social science on the level of Gladwell, or Steven Levitt, or Nate Silver. The comparisons to these authors are legitimate.Now, the negatives. I have two. Primarily, I do not want to read about pornography data. Stephens-Davidowitz loves this data, and I don't understand why. Besides the obvious turnoff, these sections did not provide any new insight to me. In addition, Stephens-Davidowitz explains late in the book about the difference between correlation and causation, but at some points he doesn't seem to understand this concept himself. Of course Google searches for hating/killing Muslims goes up while Barack Obama is making a speech about a Muslim terror attack, even if he is urging acceptance and friendship with our Muslim neighbors. That doesn't mean his urging caused people to hate Muslims more. This and similar correlations really bothered me.
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  • Sean Sullivan
    May 21, 2017
    I finished Everybody Lies in a single sitting. Not because it's short but because it's fascinating. Seth Stephens-Davidowitz presents insights gleaned from big data—Google, Facebook, Amazon, Pornhub—to entertain with counterintuitive discoveries. Each example is used to show the power, and limitations, of warehouses stacked with boxes of information and present a picture of how researchers can use big data to understand what people are really thinking. People lie to each other all the time. Espe I finished Everybody Lies in a single sitting. Not because it's short but because it's fascinating. Seth Stephens-Davidowitz presents insights gleaned from big data—Google, Facebook, Amazon, Pornhub—to entertain with counterintuitive discoveries. Each example is used to show the power, and limitations, of warehouses stacked with boxes of information and present a picture of how researchers can use big data to understand what people are really thinking. People lie to each other all the time. Especially when we're presenting our most attractive angles on social media. But the white walls of the Google Search bar have become a confessional booth, invariably revealing embarrassing worries and our strangest, and darkest, desires. At times data can present an uncomfortable picture of human nature, but the ubiquity with which men and women search for answers to questions about their genitals ought to offer some solace—along with other surreptitious google searches: we're not alone. What makes Davidowitz's book stand apart from other big data essays is its reliance on simple, and accessible tools, such as Google Trends and Adwords to make connections. I can head now to Google Trends to make relative comparisons between keywords. Or, even use Google autocomplete to see what the most popular searches are. Just now I searched "Why do I..." and Google tells me that the number one search is "Why do I feel alone." If big data can tell us anything it's that we share the same curiosities and worries as others. Davidowitz's writing is clean and clear, accessible to anyone with even a slight interest—as I had. The material's ordering presents an engrossing narrative as it moves from insights that hook, offering snapshot stories that embed information for easy recall, to big data's utilization in Silicon Valley and its potential pitfalls. I highly recommend Everybody Lies. Davidowitz concludes his book by looking at the big data and recognizing that in general most readers never make it to the last page. He's right. But my intuition tells me Everybody Lies is a statistical outlier.
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  • Josh
    May 20, 2017
    Everybody Lies by Seth Stephens-Davidowitz is a book about how big data has the potential to transform both how we understand human needs and desires at a fundamental level and how to respond to these on personal, regional and global scales. Stephens-Davidowitz begins the book by stating that our public, Facebook life is much different than our private googling. On Facebook we "Love/Adore/Admire" our loved ones and on Google we search for creative ways on how to use an ice pick. This brings Shak Everybody Lies by Seth Stephens-Davidowitz is a book about how big data has the potential to transform both how we understand human needs and desires at a fundamental level and how to respond to these on personal, regional and global scales. Stephens-Davidowitz begins the book by stating that our public, Facebook life is much different than our private googling. On Facebook we "Love/Adore/Admire" our loved ones and on Google we search for creative ways on how to use an ice pick. This brings Shakespeare to mind, "All the world's a stage, And all the men and women merely players; They have their exits and their entrances..." As much as we like to consider ourselves as independent actors, our audience impacts our actions more than we think; we are who people want us to be. So what happens when that person is Google? Stephens-Davidowitz delves deep into Google's anonymized metadata to illustrate the promise of big data as the science of the 21st century. The result is a mixed bag. Stephens-Davidowitz generates a number of Freakonomics type studies, from the amusing, what do men and women around the world google after getting pregnant, to the serious, how does racism impact elections. The problem with big data as it evolves and matures is that fundamentally science uses data to anchor our models and natural laws, not vice versa. This problem is manifest in Everybody Lies. Stephens-Davidowitz attempts to both report and conduct big data science and does not really succeed on either front. Additionally, the entire conclusion of the book feels hastily written and Stephens-Davidowitz arrogantly justifies this saying that big data suggests you aren't going to read it anyways. Everybody Lies is a worthwhile addition to the increasing body of big data literature, that just like its subject, has some growing up to do.
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  • Daniel Frank
    May 10, 2017
    A great book, by a great up-and-coming economist, on one of the most important topics of our time. The world would be truly better off if more people internalized the lessons of this book. Most of the content in Everybody Lies can be found in other places (most notably, in Seth's NYT columns), but it's nice to have all the content in one place for those unacquainted with the research.This book is at its strongest when it's analyzing search trends, specifically where conventional understanding is A great book, by a great up-and-coming economist, on one of the most important topics of our time. The world would be truly better off if more people internalized the lessons of this book. Most of the content in Everybody Lies can be found in other places (most notably, in Seth's NYT columns), but it's nice to have all the content in one place for those unacquainted with the research.This book is at its strongest when it's analyzing search trends, specifically where conventional understanding is wrong (ie see Seth's research on sexual anxiety). Seth manages to reveal a lot about humans/society that we currently have major misconceptions on. I wish Seth took this further, as there is so much information out there, but so little published on this topic. Seth cites Peter Thiel in the book, but the book could have been much more Thiel-ien.There are some minor issues with this book, but none that get in the way of the message (ie search trends on animus towards muslims does not correlate with actual hate crimes, hedge funds are 100% successfully using big data to predict the market). My only other note is that as the pioneer of much of this research, it would have been great if Seth posted a github page, and helped others get involved with this research.
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  • Stephen Yoder
    May 4, 2017
    I enjoyed the stuffing out of this book. It was a fast read. Seth has written about a pretty wonky concept--Big Data--but, in software terms, his writing style has placed a really easy, unobtrusive user interface over all of that science, statistics, and (often) massive datasets.What I'd really enjoy would be a collaboration between Mr Stephens-Davidowitz and Sudhir Venkatesh. They are both looking in some corners of our society that have not been illuminated with official statistics. It is impo I enjoyed the stuffing out of this book. It was a fast read. Seth has written about a pretty wonky concept--Big Data--but, in software terms, his writing style has placed a really easy, unobtrusive user interface over all of that science, statistics, and (often) massive datasets.What I'd really enjoy would be a collaboration between Mr Stephens-Davidowitz and Sudhir Venkatesh. They are both looking in some corners of our society that have not been illuminated with official statistics. It is important to get transparency into the difficult areas of human behavior and our own culture. This book accomplishes that goal. Pretty much everyone should read this book--people with genitals, people who were ever children, people who enjoy sports. . . the list goes on and on. The sections about child abuse & abortion hit me hard, and I believe that anyone with a soul, regardless of political affiliation, will feel the same as I did.I got an advance reading copy for the possibility of writing this review. I am grateful for that.PS -- "Too few of you, Big Data tells me, are still reading." Au contraire, Seth. I read the whole darn thing.
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  • Patrycja
    May 3, 2017
    I won this book through GoodReads giveaway. The title is not really relevant to the content. I think it is misleading the reader. This book is not as much about lying but more about data found on the internet, and author's analyses about what we search online. I think we all know that everybody lies, and that it is easier to ask some questions anonymously online, or do online search. When every person does it, we all leave the trace online. ( And that everybody lies on social media is also known I won this book through GoodReads giveaway. The title is not really relevant to the content. I think it is misleading the reader. This book is not as much about lying but more about data found on the internet, and author's analyses about what we search online. I think we all know that everybody lies, and that it is easier to ask some questions anonymously online, or do online search. When every person does it, we all leave the trace online. ( And that everybody lies on social media is also known. We all want to look happy and blessed, while in fact some may feel alone, depressed and annoyed. So this kind of data isn't too helpful for analysis). Because of the trace we leave, Seth Stephens-Davidovitz is able to analyze it and he can come up with answers to questions like: How many Americans are racist? Does advertising work? What's the best place to raise your kids? Personally I didn't find this book ground breaking, but needless it was an interesting read.
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  • Vince
    May 21, 2017
    I enjoyed this book. It reminded me of Freakonomics. I'm not sure that all the findings in this book will hold up - at times I wish the author went in to greater detail about the methodology because there were some obvious objections to some of the conclusions that the author didn't address. Like the geographic correlations have obvious statistical issues. And when he talks about searches and comparing them, it seems like it would be easy to miss searches that mean the same thing but are worded I enjoyed this book. It reminded me of Freakonomics. I'm not sure that all the findings in this book will hold up - at times I wish the author went in to greater detail about the methodology because there were some obvious objections to some of the conclusions that the author didn't address. Like the geographic correlations have obvious statistical issues. And when he talks about searches and comparing them, it seems like it would be easy to miss searches that mean the same thing but are worded slightly differently. Those issues come down to trusting that the author knows what he is doing. Also, I don't have a problem with Trump bashing, but bringing up the Trump - David Duke episode made me wonder about the quality of the fact checking. You can look in to that elsewhere and decide what you believe, but I think it's pretty uncharitable when Trump has disavowed Duke a bunch of times. Plenty of other ways to bash Trump.
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  • Amanda
    May 12, 2017
    Ever wondered if that thing you google at 4 am is just something you do? Seth Stephens-Davidowit takes what we are all thinking about but never talk about and puts it in writing. Detailed, thoughtful, and surprising, Seth Stephens-Davidowitz has a way of making even the most upsetting facts seem accessible and even normal. I'm not a data person, but i've already suggested Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are for my Book Club because it's s Ever wondered if that thing you google at 4 am is just something you do? Seth Stephens-Davidowit takes what we are all thinking about but never talk about and puts it in writing. Detailed, thoughtful, and surprising, Seth Stephens-Davidowitz has a way of making even the most upsetting facts seem accessible and even normal. I'm not a data person, but i've already suggested Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are for my Book Club because it's such a good good read for anyone who is looking for an accessible, fun, and informative popular science book that still challenges you to question what you think you know. A great conversation starter!
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  • Arun Mahendrakar
    May 23, 2017
    It's hard to imagine a book written mostly based on what people entered in Google search, but the author ingeniously used this easy-to-obtain repository to find many things about us.Obtaining an authentic source of data is key to any data analysis. He rightly argues that people are less truthful to their closest aides/partners, but disclose their honest feelings to a search engine. I'm guilty myself, so much so, that I'm cautious of what I enter in the search bar now.. well not quite, I'll proba It's hard to imagine a book written mostly based on what people entered in Google search, but the author ingeniously used this easy-to-obtain repository to find many things about us.Obtaining an authentic source of data is key to any data analysis. He rightly argues that people are less truthful to their closest aides/partners, but disclose their honest feelings to a search engine. I'm guilty myself, so much so, that I'm cautious of what I enter in the search bar now.. well not quite, I'll probably continue being myself.There's a disclaimer on what Big Data cannot do and how it should not be used. The author also warns us of jumping to conclusions just because our data set was large.I thoroughly enjoyed reading this book and will wait for Everybody (still) lies.
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  • Amber
    May 10, 2017
    I received a copy of this book through Goodreads' First Reads program. I found this to be a very readable, and mostly entertaining romp through the world of Big Data. Specifically, this focuses on what we can learn about human behavior from the data found in different areas of internet activity. As with any study of human behavior, there are some depressing, deeply concering, and downright odd things explored, but it all serves to illustrate the wide wide variety of behaviors which can be studie I received a copy of this book through Goodreads' First Reads program. I found this to be a very readable, and mostly entertaining romp through the world of Big Data. Specifically, this focuses on what we can learn about human behavior from the data found in different areas of internet activity. As with any study of human behavior, there are some depressing, deeply concering, and downright odd things explored, but it all serves to illustrate the wide wide variety of behaviors which can be studied using big data. You don't have to be a data scientist to appreciate this. A fairly fast and good read for the inquisitive mind.
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  • Alan
    May 14, 2017
    Another big data book, much like Freakonomics. I knew that Google queries were used for flu tracking, but there was so much more behind that. The author presented many interesting and counterintuitive findings. If you go searching, you can find many of the data sets discussed in the book on the author's web-site and can read is findings in more technical detail. Cool some of the sample sizes seems bit small.You should be warned. There is analysis of racial hatred and sexuality in this book. And Another big data book, much like Freakonomics. I knew that Google queries were used for flu tracking, but there was so much more behind that. The author presented many interesting and counterintuitive findings. If you go searching, you can find many of the data sets discussed in the book on the author's web-site and can read is findings in more technical detail. Cool some of the sample sizes seems bit small.You should be warned. There is analysis of racial hatred and sexuality in this book. And thus it includes many words that are not used in polite company or for children.
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  • Chris Bull
    May 15, 2017
    The future Coming from a hard science background but spending most of my career in the soft social sciences, I was frustrated by gullibility of my colleagues. Surveys were the way to go and sampling need only be the minimum needed. Even observations were a foreign idea. And for data analysis, most could not operate a spread sheet.Data and plenty of it. I only fear the monetarising of the results. We are getting dry close to the point when you can fool ALL the people.And yes, I did finish the boo The future Coming from a hard science background but spending most of my career in the soft social sciences, I was frustrated by gullibility of my colleagues. Surveys were the way to go and sampling need only be the minimum needed. Even observations were a foreign idea. And for data analysis, most could not operate a spread sheet.Data and plenty of it. I only fear the monetarising of the results. We are getting dry close to the point when you can fool ALL the people.And yes, I did finish the book.
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  • Hakan Jackson
    May 26, 2017
    I never really thought of big data that much as a social science tool. After reading this book I'm starting to think big data can do for sociology what MRI has been able to do for psychology. I'm excited to see what the future holds. I definitely can pick up the influence of Freakanomics, Malcolm Gladwell, and Stephen Pinker in this book. If you like any of those three, definitely pick up this book.
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  • Jeffrey
    May 15, 2017
    Interesting introduction to the use of Big Data in research. A lot of good information, delivered in a digestible manner, with an entertaining writing style. While the author does eventually discuss the limitations and problems with using Big Data, many of the examples given in the book as to the use of Big Data are over sold, or described in a causal manner when they are really only descriptive. This is useful in its own right, but oversells some of the product.
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  • Sarah
    May 14, 2017
    I really enjoyed this book. This book fills in the massive gap between what we report and what we search on Google and sets up Google as humanity's ultimate confessor. This book was a smart, funny, sharp, and insightful in its analysis of what Big Data can tell us about the world and our habits. I am now more conscious of how I use Google (not in a "Big Data Is Watching" way, but in my relationship to Google in general). Fantastic book.
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  • Tommy Collison
    May 24, 2017
    There have been a handful of books written on the new phenomenon of Big Data, and this one's the best. An eminently readable, funny, and accessible look at what the data can tell us, rather than an an anodyne, report on the fact that Big Data is a thing now. The third section, on the shortcomings & ethical questions of big data, is frank and, pleasingly, doesn't feel like it's something tacked onto the end. Stephens-Davidowitz is one to watch.
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  • Carol Checkler
    May 23, 2017
    This book is jammed packed with new tools of how to dissect the human psyche. Many of the resources and ideas could be further developed into powerful tools applicable to just about everything in life, education, health care, criminal system, marketing, to name a few. I finished the book with heightened curiosity about Big Data, and am searching for more good reads on this topic.
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  • Dolly
    May 13, 2017
    This book is both data-rich and funny ... at the same time! The author is a PhD in economics from Harvard using cutting edge methods to study human behavior. Boy, is he finding great stuff ... and by great, I mean the stuff we need to know but would otherwise would never know. An essential and enjoyable read!
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  • David
    May 16, 2017
    While this book reviews some interesting studies, I felt like it could be 1/2 as long. If you're already familiar with other popular behavioral science books and have a basic understanding of things like how Google ranks pages, much in this book will be a review.
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  • Robbie Forkish
    May 18, 2017
    The author writes in an engaging fashion about new insights into the human condition that emerge from big data studies. He uses sources such as google searches, Facebook stats, porn site searches, voting records, tax records, subscription data and more to gain convincing and surprising perceptions on what we worry about and what motivates us. The book is new, and the author's research is in the news as he discovered, using a novel technique, that Trump's election was driven by racism much more t The author writes in an engaging fashion about new insights into the human condition that emerge from big data studies. He uses sources such as google searches, Facebook stats, porn site searches, voting records, tax records, subscription data and more to gain convincing and surprising perceptions on what we worry about and what motivates us. The book is new, and the author's research is in the news as he discovered, using a novel technique, that Trump's election was driven by racism much more than had been realized. Highly recommended.
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  • David W. Parker
    May 17, 2017
    Great read about big data sets, why what we ask google is different than what we tell researcher and how that changes economics and social research (if you're not easily offended by references to porn data). If you're interested in Data Science application, it's a great read.
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  • Emily
    April 15, 2017
    This book is in that particular genre where the author tries to make his or her area of expertise (often physics for some reason, though clearly not in this case) palatable and accessible to the "common (wo)man." These types of books fail when the author doesn't dumb it down enough or dumbs it down too much. Stephens-Davidowitz's area is economics/social science by way of Big Data, and he dumbs it down just the right amount.At the beginning of the book, my inner skeptic was anxiously asking abou This book is in that particular genre where the author tries to make his or her area of expertise (often physics for some reason, though clearly not in this case) palatable and accessible to the "common (wo)man." These types of books fail when the author doesn't dumb it down enough or dumbs it down too much. Stephens-Davidowitz's area is economics/social science by way of Big Data, and he dumbs it down just the right amount.At the beginning of the book, my inner skeptic was anxiously asking about correlation vs causation and how people can know they're asking the right questions of the right data. By the end of the book, Stephens-Davidowitz had satisfactorily addressed most of my initial concerns and provided some insight into data science, social science, and some aspects of human nature along the way. Plus, the book made me laugh (well, chuckle) out loud more than a few times, which means I was pretty engaged and is not bad for a book about data science.Some notes: - The subtitle ("Big Data, new data, and what the internet can tell us about who we really are") is slightly misleading. While much of the book does rely on search queries (predominately Google) and Twitter and Facebook updates, plenty of the analysis and studies rely on non-internet data sources. Stephens-Davidowitz is clearly excited about all of the new ways to use all of the new internet data, but the overall focus of the book is on Big Data of all kinds and its powers and drawbacks.- Some chapters illustrate the fact that people admit things on the internet they would not admit elsewhere. Issues addressed include porn preferences and racism, both discussed in detail, and child abuse, suicide, and similar, discussed in less detail. Although the possible conclusions range from unsavory to downright depressing, the topics are relevant to addressing the book's points about data and social science; however, worth noting because some readers will be sensitive to these topics.(Thank you, Dey Street Books and GoodReads for the ARC.)
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  • Kathleen
    May 26, 2017
    I read this book after the author was interviewed on NPR's Hidden Brain podcast. I enjoyed the book, though I can't say after reading it I took much away. There wasn't anything that really wowed me, but Seth's results and discussions from various data analysis were interesting.
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  • Kendall
    May 25, 2017
    The only nonfiction book I have ever binge-read. I now know that when a hurricane is approaching people are 7x more likely to buy strawberry poptarts, among other more meaningful things. It reminded me a lot of Dataclysm, which I also really enjoyed, but was easier to read.
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  • Joshua
    May 21, 2017
    A fascinating look into the nature of data science and how the explosion of data generated by the internet is telling us new things about ourselves and turning social scientists into actual scientists. A worthy successor to Freakonomics.
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