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664 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
664 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
This is a fascinating read. The author wrote his PhD using Google data and it is a fantastic read. Much like Freakonomics opened up the questions that economists can answer, this book helps move the discussion forward about what we really do online.
A wide-ranging, provocative, entertaining examination of big data that offers an ambitious framework for what big data can and should do--while also evidencing awareness of what it cannot and should not do. The title and promotion center around the "Everybody Lies" theme--with Seth Stephens-Davidowitz describing Google searches as a "digital truth serum" that allows us to see, for example, the extent of racism by following searches for racist jokes. But the book goes much further in identifying and providing examples of three other uses of big data: (1) allowing us to use new types of data, (2) zooming on on very particular places or cases without losing the ability to discern in a smaller sample, and (3) providing an easy way to conduct A/B tests and other experiments.
In the course of this framework, Stephens-Davidowitz provides a constant stream of examples drawn from economics (including his own work), social science, and elsewhere to illustrate the many ways that "big data", much but not all of it Google searches, has helped us learn about what people are really thinking and doing.
But Stephens-Davidowitz also describes the problems with big data--the curse of dimensionality that leads to overfitting models that work really well in sample but terribly outside it (e.g., predicting stocks) and the overemphasis on what is measurable (e.g., moneyball-oriented baseball teams ending up with inefficiently weak fielders because they were focused on measurable batting statistics). And he also has warnings on privacy and more.
Strongly recommended.
In the course of this framework, Stephens-Davidowitz provides a constant stream of examples drawn from economics (including his own work), social science, and elsewhere to illustrate the many ways that "big data", much but not all of it Google searches, has helped us learn about what people are really thinking and doing.
But Stephens-Davidowitz also describes the problems with big data--the curse of dimensionality that leads to overfitting models that work really well in sample but terribly outside it (e.g., predicting stocks) and the overemphasis on what is measurable (e.g., moneyball-oriented baseball teams ending up with inefficiently weak fielders because they were focused on measurable batting statistics). And he also has warnings on privacy and more.
Strongly recommended.
I'm vacillating between 2 and 3 stars here. A friend recommended this to me when I posted my outrage and disbelief about the senseless killing of Ahmaud Arbery (in case you don't know). She said that she didn't know how truly racist America was until she read this book. I took away the same conclusion - in fact, this is the same finding that spurred Stephens-Davidowitz to write this book in the first place - but I didn't take away much else.
I think another reviewer said it best - this book is trying a little too hard to be Version 2.0 of [b:Freakonomics: A Rogue Economist Explores the Hidden Side of Everything|1202|Freakonomics A Rogue Economist Explores the Hidden Side of Everything|Steven D. Levitt|https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1550917827l/1202._SX50_.jpg|5397] (the author even acknowledges this effort in the conclusion). I understand the sentiment, as big data already has been the source of much new knowledge, business strategies, etc. But I frankly don't think that the other anecdotes and insights were anything to write home about. I was certainly surprised to find concrete proof of America's hidden racism (the biggest reason for this finding is the number of people who Google racist slurs or questions, including the n-word), but it doesn't at all surprise me that people lie on social media/surveys/real-life and give all of their nasty and inconvenient truths to Google instead.
The author also spends quite a bit of time explaining "big data" query and survey methods, so this might be interesting for those who are not familiar (e.g. A/B testing, doppelganger searches).
Anyways, this was a moderately interesting audiobook to keep me company on my quarantine walks, but I probably wouldn't recommend it to many others. You'd be better off picking up Freakonomics again!
I think another reviewer said it best - this book is trying a little too hard to be Version 2.0 of [b:Freakonomics: A Rogue Economist Explores the Hidden Side of Everything|1202|Freakonomics A Rogue Economist Explores the Hidden Side of Everything|Steven D. Levitt|https://i.gr-assets.com/images/S/compressed.photo.goodreads.com/books/1550917827l/1202._SX50_.jpg|5397] (the author even acknowledges this effort in the conclusion). I understand the sentiment, as big data already has been the source of much new knowledge, business strategies, etc. But I frankly don't think that the other anecdotes and insights were anything to write home about. I was certainly surprised to find concrete proof of America's hidden racism (the biggest reason for this finding is the number of people who Google racist slurs or questions, including the n-word), but it doesn't at all surprise me that people lie on social media/surveys/real-life and give all of their nasty and inconvenient truths to Google instead.
The author also spends quite a bit of time explaining "big data" query and survey methods, so this might be interesting for those who are not familiar (e.g. A/B testing, doppelganger searches).
Anyways, this was a moderately interesting audiobook to keep me company on my quarantine walks, but I probably wouldn't recommend it to many others. You'd be better off picking up Freakonomics again!
I really enjoyed the data and correlations in this book and found them fascinating. I wish the author would’ve trusted the reader a bit more in this regard, however. It seems that he didn’t trust that we’d find the data compelling enough, so he inserted himself into the narrative over and over. I found some of these insertations funny and I’d probably enjoy having a beer with the guy, but the thing is the data was compelling enough. I think if someone’s going to pick up a book about big data and google searches, you can rest assured they’re nerdy enough to be enthralled by the contents alone.
informative
inspiring
slow-paced
I really enjoyed Davidowitzs writing style. It was easy to understand even for a nonnative speaker.
The book was very anecdotal at times which I found to be a little too much.
Nevertheless I think the book taught me a lot and I feel like my understanding of data science increased (it’s still very basic though).
It took me a while to get to the end of the book but against all likelihood I finished it and I enjoyed it.
Luckily for the author my rating of the book is solemnly based on the writing style and on how interesting the content was to me as I can’t rate the information given in the book due to a lack of knowledge.
⭐️⭐️⭐️
The book was very anecdotal at times which I found to be a little too much.
Nevertheless I think the book taught me a lot and I feel like my understanding of data science increased (it’s still very basic though).
It took me a while to get to the end of the book but against all likelihood I finished it and I enjoyed it.
Luckily for the author my rating of the book is solemnly based on the writing style and on how interesting the content was to me as I can’t rate the information given in the book due to a lack of knowledge.
⭐️⭐️⭐️
A discussion of different uses and limitations of Big Data. The title doesn't really apply to most of the content of the book, and to be honest the "everybody lies" parts were much less interesting to me than everything else. But still, the actual topic of big data interested me.
The upshot of this book is not that big data is the holy grail. Rather, the recurring theme in all of Stephens-Davidowitz's interesting examples is just that most self-reporting is awful.
I'm still skeptical about the big data revolution--and this book doesn't really focus on implicit bias in analysis of large data sets--but the conventional research methods of social sciences are amusingly torn to pieces (much like advertising ROI was absolutely shredded in the digital age where measurement was no longer entirely by gut).
I'm still skeptical about the big data revolution--and this book doesn't really focus on implicit bias in analysis of large data sets--but the conventional research methods of social sciences are amusingly torn to pieces (much like advertising ROI was absolutely shredded in the digital age where measurement was no longer entirely by gut).
informative
medium-paced
I was a little disappointed with this one.
Sure there were some good bits about the potential of big data, especially Google search data, and its ability to transform the "soft" social sciences into something more like a hard science. There were some interesting points and anecdotes about the effect this would have on the development of philosophy, politics, commerce, sport and medicine.
But the inordinate fascination of the author with sexual perversity made reading the book feel like the mental equivalent of wading through sewage. I listened to the audiobook, so it felt like someone incessantly piping litanies of putrid filth into my head. I fast-forwarded to try and avoid the disgusting imagery but half an hour later he was still harping on about some deviant sexual fetish or other.
There are many worthwhile books exploring the potential of Big Data. I wouldn't recommend this one. The payoff is just not worth the disgust factor.
Sure there were some good bits about the potential of big data, especially Google search data, and its ability to transform the "soft" social sciences into something more like a hard science. There were some interesting points and anecdotes about the effect this would have on the development of philosophy, politics, commerce, sport and medicine.
But the inordinate fascination of the author with sexual perversity made reading the book feel like the mental equivalent of wading through sewage. I listened to the audiobook, so it felt like someone incessantly piping litanies of putrid filth into my head. I fast-forwarded to try and avoid the disgusting imagery but half an hour later he was still harping on about some deviant sexual fetish or other.
There are many worthwhile books exploring the potential of Big Data. I wouldn't recommend this one. The payoff is just not worth the disgust factor.
Anecdotal, and speculative at best. Reader's Digest level read in a way that makes it a bit cringe-worthy.