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662 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Steven Pinker, Seth Stephens-Davidowitz
3.82 AVERAGE
662 reviews for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are
Steven Pinker, Seth Stephens-Davidowitz
3.82 AVERAGE
I think the idea of big data is fascinating! Unfortunately, this book didn’t really connect all the dots for me. I don’t really agree with some of the conclusions that the author comes too. And also questioned some of his studies. But it did bring up some interesting points.
Don’t worry about spending your time on this one.
Don’t worry about spending your time on this one.
Super interesting trivia, and really great comparisons of intuition versus what people really think when no one is looking.
i think if i weren’t so statistically challenged, i’d find work in data science very compelling.
i think it’s more likely i’ll try my best to learn and understand it and figure out how to best share its existence with others so they might be compelled, moved, and informed themselves.
a lot of reviews seemed somewhat dissatisfied by the often light or breezy tone this book takes. it, after all, seeks not just to educate but to entertain as well. to that, i say that this book does what it sets out to do, and to expect or ask anything else of it would suggest you’re looking for a different one. if you’re going to be offended by statistical examinations of porn searches (and what this might mean for human sexuality), or even more surprisingly criticize this as some gimmicky appeal to men (as if women don’t also watch porn or have sex /gasp), then this probably isn’t for you.
everybody lies has funny moments, relatable moments, sad moments, but above all it offers a broad and comprehensive glimpse into how much of humanity and society might be better understood (or affected) by big data. seth stephens-davidowitz writes in an accessible and slightly jocular voice, occasionally on perhaps more crude subjects, but ultimately creates a genuinely enjoyable and extremely interesting book.
i think it’s more likely i’ll try my best to learn and understand it and figure out how to best share its existence with others so they might be compelled, moved, and informed themselves.
a lot of reviews seemed somewhat dissatisfied by the often light or breezy tone this book takes. it, after all, seeks not just to educate but to entertain as well. to that, i say that this book does what it sets out to do, and to expect or ask anything else of it would suggest you’re looking for a different one. if you’re going to be offended by statistical examinations of porn searches (and what this might mean for human sexuality), or even more surprisingly criticize this as some gimmicky appeal to men (as if women don’t also watch porn or have sex /gasp), then this probably isn’t for you.
everybody lies has funny moments, relatable moments, sad moments, but above all it offers a broad and comprehensive glimpse into how much of humanity and society might be better understood (or affected) by big data. seth stephens-davidowitz writes in an accessible and slightly jocular voice, occasionally on perhaps more crude subjects, but ultimately creates a genuinely enjoyable and extremely interesting book.
I would have rated this more highly if he would've left out the little snippets showing his political bias. It really started making me question whether his other assertions were founded more with other biases in mind or based on good research.
informative
fast-paced
Enjoyable book. Contrary to his hypothesis, I made it to the end!
A pretty decent book but felt like a BTEC freakonomics, even down to the style and tone of writing.
4.5 Stars. The information in this book presented both devastating (racism, abuse) and hilarious (porn proclivities) conclusions about who we really are, based in large part on data from unhindered google searches. I wonder whether data I provide with my goodreads account will be used for some profound conclusion about human behaviors. Very quick read, highly interesting.
This is a very easy book to read. The whole book is about big data with a lot of practical examples of how it's used to solve everyday problems. This book is not a primer on developing big data datasets but shows the reader how data scientists make use of the data and some of the insights they can get from big data.
This book deals with how big data can be used to learn about people at a particular place and time. I learnt a lot of things about people and society with a lot of accepted norms being shown to be false by data. Oh yes, people always think the best (or worse) of themselves and others but the data show a totally different picture. Hence the title, everyone lies...except to a search engine.
Besides all the good new research that can be done with big data, the author shows the limitations of using big data and the difficulty of using correlation for causation. The type of datasets is important. More data is not always the answer but the right kind of data is important.
It's a fun book and I highly recommend it, even if you are not a data scientist.
This book deals with how big data can be used to learn about people at a particular place and time. I learnt a lot of things about people and society with a lot of accepted norms being shown to be false by data. Oh yes, people always think the best (or worse) of themselves and others but the data show a totally different picture. Hence the title, everyone lies...except to a search engine.
Besides all the good new research that can be done with big data, the author shows the limitations of using big data and the difficulty of using correlation for causation. The type of datasets is important. More data is not always the answer but the right kind of data is important.
It's a fun book and I highly recommend it, even if you are not a data scientist.
I’m surprised I hadn’t heard of this book before coming across it at a used book sale recently, since it came out in 2017 and covers human behavior topics in which I’m interested, with a unique angle.
I learned numerous things from the book, including the story about predicting horse race success based on the size of internal organs, and the fact that Floridians apparently stock up on strawberry Pop Tarts before hurricanes.
Stephens-Davidowitz is a clear and engaging writer, in the tradition of [a:Steven Pinker|3915|Steven Pinker|https://images.gr-assets.com/authors/1235758085p2/3915.jpg], who wrote the foreword to this book, but with a slightly quirkier tone. The big picture view that he conveys about the use of not only large quantities of data but innovative sources of data is truly fascinating.
On the other hand, some questions remain in my mind: The author presents valid evidence that the data from Google searches really does correspond to patterns in the world. But why exactly do people search for things that are not even searchable questions such as “I hate cold weather” (p. 112)? Maybe a study should be done to explain why people don’t at least make an effort to phrase it in the form of a question? I understand that the data doesn’t lie, but maybe it’s only capturing a strange subset of the behavior, or maybe peoples’ habits will change over time.
Also, there’s an emphasis on searches for offensive or threatening terms, and also on sexual topics, mainly because this seems to be what “Everybody Lies” most about. But if that’s the case, can we really trust the data from people who are logged in to PornHub with presumably authentic accounts, having accurately provided their gender and other personal info? Or are more people just finding videos to watch for free? Then there’s the study where teachers were paid for attendance that concluded that “The results were remarkable.” (p. 209). I’m not sure it’s so remarkable that people do better work if you pay them more.
The commentary on companies’ excessive use of A/B testing to basically exploit their target audience is spot on, and although the author allows that big data also benefits consumers in some cases, the power to abuse it is clearly in the hands of those who can pay for it.
Overall, I enjoyed the book; I’d say it was 3 to 4 star, and I’ll round up for polished execution.
I learned numerous things from the book, including the story about predicting horse race success based on the size of internal organs, and the fact that Floridians apparently stock up on strawberry Pop Tarts before hurricanes.
Stephens-Davidowitz is a clear and engaging writer, in the tradition of [a:Steven Pinker|3915|Steven Pinker|https://images.gr-assets.com/authors/1235758085p2/3915.jpg], who wrote the foreword to this book, but with a slightly quirkier tone. The big picture view that he conveys about the use of not only large quantities of data but innovative sources of data is truly fascinating.
On the other hand, some questions remain in my mind: The author presents valid evidence that the data from Google searches really does correspond to patterns in the world. But why exactly do people search for things that are not even searchable questions such as “I hate cold weather” (p. 112)? Maybe a study should be done to explain why people don’t at least make an effort to phrase it in the form of a question? I understand that the data doesn’t lie, but maybe it’s only capturing a strange subset of the behavior, or maybe peoples’ habits will change over time.
Also, there’s an emphasis on searches for offensive or threatening terms, and also on sexual topics, mainly because this seems to be what “Everybody Lies” most about. But if that’s the case, can we really trust the data from people who are logged in to PornHub with presumably authentic accounts, having accurately provided their gender and other personal info? Or are more people just finding videos to watch for free? Then there’s the study where teachers were paid for attendance that concluded that “The results were remarkable.” (p. 209). I’m not sure it’s so remarkable that people do better work if you pay them more.
The commentary on companies’ excessive use of A/B testing to basically exploit their target audience is spot on, and although the author allows that big data also benefits consumers in some cases, the power to abuse it is clearly in the hands of those who can pay for it.
Overall, I enjoyed the book; I’d say it was 3 to 4 star, and I’ll round up for polished execution.