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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
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
Seth Stephens-Davidowitz
3.82 AVERAGE
informative
fast-paced
It was interesting to hear the examples but nothing very new for me. At some moments the author was a bit off in the jokes and this bothered me but not to great extent.
I picked up this book to get the interesting facts that Stephens-Davidowitz learned from his analyses of this revealing dataset. That said, there is also plenty of basic introduction to data collection and research methodology, which might be a bit tedious for anyone who is already familiar with this material. However, I appreciated the attention to basics when it came to statistical analysis, an area where I don’t have the same background knowledge or experience. The author also spends a good bit of time trying to convince skeptics on one side that big data is useful, and on the other side, warning evangelists of the limitations. A big dataset can actually be an encumbrance if you don’t know what questions to ask of it. However, I sometimes took issue with the way the author tried to present information in an accessible way. Comparing a large dataset to your Grandma’s lifetime of collected wisdom is more harmful than helpful because only one of those things is based on verifiable numbers rather than impressions. read more
informative
medium-paced
Interesting. I think sometimes he alludes to causation when it’s just correlation (and then discusses how that’s bad), but the correlations are interesting. I like the idea of having another data set.
Interesting facts, but a little scattered
I first heard about Everybody Lies from the podcast Fresh Air. I was deeply interested in the concept of a data scientist using the data from Google searches to generate insights about human behavior.
It was an interesting concept, but doesn't quite stick the landing in terms of execution.
As I progressed through the book, one thing that I kept trying to figure out was if the intention of this book was to unearth humanity's deep dark secrets or a guide to understanding and demystifying data science. The result was somewhere in between.
Don't get me wrong, I enjoyed learning things like how American Pharaoh was destined to be a Triple Crown winner or whether what college you go to really does correlate with greater success in the long-term.
But the author just sets these up as examples of a concept of data science. I felt like the back and forth did not give the insights or the data science concepts full justice.
The book starts off a little scatterbrained in the first few chapters but really begins to pick its stride in the later chapters. I genuinely feel like I have a fundamental understanding of the methodologies of data science as well as a few cool facts to drop at my next cocktail party. My advice to anyone reading is to stick with the book because as unfocused as it may seem, you will still learn something.
I first heard about Everybody Lies from the podcast Fresh Air. I was deeply interested in the concept of a data scientist using the data from Google searches to generate insights about human behavior.
It was an interesting concept, but doesn't quite stick the landing in terms of execution.
As I progressed through the book, one thing that I kept trying to figure out was if the intention of this book was to unearth humanity's deep dark secrets or a guide to understanding and demystifying data science. The result was somewhere in between.
Don't get me wrong, I enjoyed learning things like how American Pharaoh was destined to be a Triple Crown winner or whether what college you go to really does correlate with greater success in the long-term.
But the author just sets these up as examples of a concept of data science. I felt like the back and forth did not give the insights or the data science concepts full justice.
The book starts off a little scatterbrained in the first few chapters but really begins to pick its stride in the later chapters. I genuinely feel like I have a fundamental understanding of the methodologies of data science as well as a few cool facts to drop at my next cocktail party. My advice to anyone reading is to stick with the book because as unfocused as it may seem, you will still learn something.
A seminal book
I believe this book will have a similar impact as the Freakomics - which this author admires. I am sure google search and other data from internet usage is going to have profound affect on the field of social Sciences. Great read.
I believe this book will have a similar impact as the Freakomics - which this author admires. I am sure google search and other data from internet usage is going to have profound affect on the field of social Sciences. Great read.
4.4
Excellent read. It appears this may be the welcome bolster that human sciences need - data, specifically- data that largely subverts social desirability bias based on the premise that we lie to everyone except, perhaps, our internet explorers.
There’s all sorts of wild data in this book and it’s quite fascinating to apply the principals of data analysis to qualitative questions. Although, as @cups has been exploring, there must be consideration for the implicit biases built into analytical systems and I think that could be relevant here. Also, mentioned are the ethical implications that might arise from implementations based on this kind of data mining.
I was reminded of ‘Invisible Women’ whilst reading- these analysis approaches will no doubt be welcome in the context of plugging long neglected data gaps.
Super interesting all round but weak ending imo. Unsure if purposeful following mention of few bothering economics books to the end but, even so, it was weak. Some ppl are saying it’s too like Freakonomics. Not read that and THUS can’t comment.
Excellent read. It appears this may be the welcome bolster that human sciences need - data, specifically- data that largely subverts social desirability bias based on the premise that we lie to everyone except, perhaps, our internet explorers.
There’s all sorts of wild data in this book and it’s quite fascinating to apply the principals of data analysis to qualitative questions. Although, as @cups has been exploring, there must be consideration for the implicit biases built into analytical systems and I think that could be relevant here. Also, mentioned are the ethical implications that might arise from implementations based on this kind of data mining.
I was reminded of ‘Invisible Women’ whilst reading- these analysis approaches will no doubt be welcome in the context of plugging long neglected data gaps.
Super interesting all round but weak ending imo. Unsure if purposeful following mention of few bothering economics books to the end but, even so, it was weak. Some ppl are saying it’s too like Freakonomics. Not read that and THUS can’t comment.
You can clearly see the impact of Freakonomics on this book. But all in all, a pretty interesting take on how to see the world through Data Analytics.
The author propositions the book as a new way to understand data, but actually just lists facts he found using Google Analytics.
An excellent book to get an introduction into what Big Data is, and how it has grown and will continue to grow as data becomes bigger and bigger. The author uses personal experience and fascinating case studies to portray the impacts of Big Data with relation to sports, economics (or lack there of), and the social sciences.
My only criticism is only that the author seems to be a bit taken with himself and his place in the Big Data world. He is very proud of himself and this is a bit vexatious as a reader, however it is not so bad as to take away from how enjoyable and compelling the text can be.
I strongly recommend Everybody Lies to anybody with even a passing interest in Big Data. It is a quick, fun read and you will definitely learn something.
My only criticism is only that the author seems to be a bit taken with himself and his place in the Big Data world. He is very proud of himself and this is a bit vexatious as a reader, however it is not so bad as to take away from how enjoyable and compelling the text can be.
I strongly recommend Everybody Lies to anybody with even a passing interest in Big Data. It is a quick, fun read and you will definitely learn something.
I don't know if this was revolutionary or not, it seemed like a rehash of many books going around - what we can learn from big data. Some of it was random cool facts. Some of it invites big questions for our future as a species. I think big data might be the next major revolution, in the lines of the printing press, radio, television, and the internet. It's already playing a big part in business decisions, policy making, medical practice, sports, and many other fields, but most of us are unaware of it. I think Everybody Lies is a good introduction and overview of the topic, but I do think the author places too much trust in people's honesty with Google searches. He sounds like he thinks he's found the golden egg of psychology, but it's naive to think that people even know themselves well enough or act consistently enough when making online searches, such that we could understand the core of the human psyche. For now, though, big data can squeeze billions of extra dollars out of economies, and for that alone it will never go away.