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663 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are
Seth Stephens-Davidowitz
3.82 AVERAGE
663 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are
Seth Stephens-Davidowitz
3.82 AVERAGE
An interesting book using Big Data to glimpse on human behaviour. The author has interesting ideas although not that original. The examples are really interesting and the methodologies used to answer his questions are impressive. However, this book lacks philosophical ideas and many arguments are not discussed in depth.
Everybody Lies, but we knew this right?
I work in Digital Marketing so I am always interested in how people behave on and off social media, especially the things people search for. My friend recommended I give this book a read because I might enjoy it.
I have to say, I did enjoy reading about the different things people search about and how Big Data can teach us a lot about human behavior. While I did enjoy reading about some of the insightful data Seth presented, I wished it could have been better presented. I know it is hard presenting hard data and you need to break the monotony and keep things interesting, however, I felt the data could have been better presented. Maybe it is because I am so used to Malcolm Gladwell's writing but I really appreciate when authors are able to present data in an engaging way.
If you are looking for a great conversation starter at a cocktail event, this is the book for you. If you work in digital market, you might also appreciate this book.
I work in Digital Marketing so I am always interested in how people behave on and off social media, especially the things people search for. My friend recommended I give this book a read because I might enjoy it.
I have to say, I did enjoy reading about the different things people search about and how Big Data can teach us a lot about human behavior. While I did enjoy reading about some of the insightful data Seth presented, I wished it could have been better presented. I know it is hard presenting hard data and you need to break the monotony and keep things interesting, however, I felt the data could have been better presented. Maybe it is because I am so used to Malcolm Gladwell's writing but I really appreciate when authors are able to present data in an engaging way.
If you are looking for a great conversation starter at a cocktail event, this is the book for you. If you work in digital market, you might also appreciate this book.
A fascinating look at the information that can be determined using Big Data, particularly Google search Data, about what people search for as opposed to what they say they are thinking and feeling. Be prepared for a lot of discussion of sexual practices, racism, questionable parenting techniques, and other topics people usually don't discuss openly, but that is where the data available diverges the most from the public persona. Also fascinating were the discussion of what Big Data research can't, and probably shouldn't, do. An interesting and informative read in the mold of Malcolm Gladwell and Steven Levitt, that does a good job of informing and entertaining the reader. I received a free ARC of this book through Goodreads First Reads giveaways.
I wanted to like this book. The concept, that what we google is telling the world fascinating things about us, and that analyzing this googling can predict presidential elections etc... it’s interesting. Unfortunately, it’s another heteronormative white man writing a book, and I soon want to punch him in the face. You know what he wants to reveal with his superpower? HOW MANY MEN ARE ACTUALLY GAY IN AMERICA. Dan Savage needs to give this guy a shaking, because this author thinks that everyone who looks at gay porn is gay. Women, he allows, just like lesbian porn, so it doesn’t work on them, but men, if you google gay porn, you must be gay. Sure, some people are bi, but otherwise, gay. This guy is a social scientist who doesn’t think human sexuality is complicated. Also, he clearly thinks that this is the best way to keep his book on big data interesting.
informative
reflective
medium-paced
This made me laugh, snort, and exclaim, on multiple occasions, in public. A very accessible and pop-sciency introduction to data science through the lens of uncovering human behaviour.
I thought many of the ideas presented about alternative means of gathering data were interesting. Using Google searches to discover early symptoms of disease is a quite a leap. I could have done without the references to his brother!
So this book will be one of the first that I DNF'd in under 50 pages, but am still giving 2 stars to.
I'm giving it 2 stars because I think Stephens-Davidowitz is probably right; search data is a gold mine into the human psyche, and far more telling than anything we will admit to on a survey.
But I don't think Stephens-Davidowitz gave any respect to his readers' knowledge of statistical analysis, or scientific processes in general. He finds a set of data, but it doesn't support his theory. So he finds another set of data, but that also doesn't support his theory. And so he continues until he finds some shred of evidence that his theory may have some plausibility, but then immediately weights it higher than all other data. Because it obviously, is the best piece. He also confuses relationships between cause and effect items, making leaps and assumptions no paper could ever get away with.
And that's the truth about this book: it was a paper he couldn't get peer reviewed. So instead he turned it into a book to sell to the masses. Because nothing says screw you like making money on the paper your peers wouldn't support.
I'm sure there's some great tidbits in here. And I hope that there are thousands of people currently working on search data as the next big insight. But this isn't where I want to start with it. All of this being said...I won't judge if you do.
I'm giving it 2 stars because I think Stephens-Davidowitz is probably right; search data is a gold mine into the human psyche, and far more telling than anything we will admit to on a survey.
But I don't think Stephens-Davidowitz gave any respect to his readers' knowledge of statistical analysis, or scientific processes in general. He finds a set of data, but it doesn't support his theory. So he finds another set of data, but that also doesn't support his theory. And so he continues until he finds some shred of evidence that his theory may have some plausibility, but then immediately weights it higher than all other data. Because it obviously, is the best piece. He also confuses relationships between cause and effect items, making leaps and assumptions no paper could ever get away with.
And that's the truth about this book: it was a paper he couldn't get peer reviewed. So instead he turned it into a book to sell to the masses. Because nothing says screw you like making money on the paper your peers wouldn't support.
I'm sure there's some great tidbits in here. And I hope that there are thousands of people currently working on search data as the next big insight. But this isn't where I want to start with it. All of this being said...I won't judge if you do.
Alternative title: "My job is super serious and important now: Please, please believe me"
Jokes aside, this was far from a bad book. It basically delved into a lot of examples of statistical analysis using large sets of data that are now available thanks to the proliferation of the internet. Most of the ideas here aren't really that ground-breaking though, despite what the author might have you believe. He also seemed to have had a complex about the validity of his work since there were numerous statements either implying or outright asserting that this method of data analysis was superior to other methods such as surveys and studies. On the one hand, he made quite a few good points and I even agreed to a large extent with his theory, however, his paranoia about the validity of his work was also somewhat justified in that there were numerous issues with either the source of his data, the interpretation of the data or using logical fallacies when trying to understand the data.
While there were a handful of somewhat interesting examples, I was mostly quite bored with this book. There was a surprisingly long section regarding human sexuality based on porn searches which might raise the eyebrows of more prudish people, but what I found most illuminating about this section was how little I cared about other people's sexuality. What people get their rocks off to, while voyeuristically interesting, is ultimately pretty useless information unless you're in the business of making porn. And that's the biggest lesson I learned from this book: People love to hear about what "normal people" do or how the "average person" behaves, but what all this ultimately does is lead to false expectations and faulty assertions.
The biggest issues with this book that showcase just how misleading most of the examples are, come from the information the author doesn't point out. Most of the data was clearly from American users and based in a very American context. I heavily suspect that a lot of the data, especially the porn data, was very dubious considering how much emphasis many people place on their privacy. Being ignorant of search habits such as searching for things because they pertain to someone else, not necessarily the person doing the search. And the biggest one, which even the author mentions in the last section, is people's inclination to confuse correlation with causation when trying to interpret this kind of data and which even the author managed to do with some of his examples.
Objectively, this is a very scientifically and logically flawed book which I'm worried many people will fall for due to the scandalous and wide-reaching nature of many of the examples. I'll admit, even I found some of the information interesting, but as I already mentioned, ultimately pointless. The last section was probably the most interesting though since it tackled some of the issues that this kind of 'science' is prone to having. I also disliked the tone of the book, mostly thanks to the author being so self-conscious about his work while trying desperately to tout his own importance. Not really a book I'd recommend to anyone, but which wasn't a total waste of time either.