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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
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
Seth Stephens-Davidowitz
3.82 AVERAGE
The premise was interesting and left me with plenty of ideas I wanted to try with big data. The last chapter was a little lackluster, but overall, this was a fun and easy read. Good material for people who need an intro to the many uses of big data.
Insightful and very interesting introduction to those who have a preliminary idea about big data and its application
meh...He says some things I did not find convincing, but it's an interesting read.
The suggestion that everybody lies is almost as shocking as the suggestion that [b:Everyone Poops|133547|Everyone Poops|Taro Gomi|https://images.gr-assets.com/books/1347679347s/133547.jpg|878180]. Please say it isn't so!
But that isn't really what this book is about. It is about the idea that you can use "big data" from Google searches and other on-line activity to learn things about people that would be difficult or impossible to learn in other ways. Lots of interesting results are shown, so it is a fun read. Especially fun when the results seem to confirm my biases (such as that [a:Sigmund Freud|10017|Sigmund Freud|https://images.gr-assets.com/authors/1406688955p2/10017.jpg] was wrong about almost everything.) But many of the results have to be hedged with "It seems like ..." or "Maybe this implies ..." and so forth. It is often impossible to know what people were really thinking when they typed some search term. So while this isn't pseudo-science, it isn't real science either, but more of a proto-science.
But that isn't really what this book is about. It is about the idea that you can use "big data" from Google searches and other on-line activity to learn things about people that would be difficult or impossible to learn in other ways. Lots of interesting results are shown, so it is a fun read. Especially fun when the results seem to confirm my biases (such as that [a:Sigmund Freud|10017|Sigmund Freud|https://images.gr-assets.com/authors/1406688955p2/10017.jpg] was wrong about almost everything.) But many of the results have to be hedged with "It seems like ..." or "Maybe this implies ..." and so forth. It is often impossible to know what people were really thinking when they typed some search term. So while this isn't pseudo-science, it isn't real science either, but more of a proto-science.
This was so fascinating! I'm a nosy person, so I especially loved taking a deep look into the "digital truth serum" of the internet and learning about the statistics behind what people search for online. Besides the juicy details about what is revealed in people's Google searches, this book contains tons of engaging examples of correlations found through looking at big data, about different factors that influence our lives, how advertisers and other corporations use big data to figure out how to hook us more effectively, and the drawbacks and dangers of using big data. There's also a lot of disturbing information about what prompts things like racist Google searches to increase. I found this book super interesting and highly recommend it! I listened to the audiobook, but I would suggest reading the print version instead, as there are a lot of charts and graphs that it would have been nice to look at as I was reading, and the narrator is a bit monotone and really doesn't add anything special to to text.
*Used for Read Harder 2018 prompt "A book of social science."
*Used for Read Harder 2018 prompt "A book of social science."
informative
slow-paced
Hard to tell if the author does good science because he does such uninteresting writing. I can imagine another book that could be so pleased with itself and, at the same time, so calculatingly composed to fulfill a contractual obligation. There is very little that is remarkable here, except for perhaps the author's obsession with porn. But even those endlessly prurient sections felt like someone trying to get more clicks for a lightweight article rather than actually contributing to the overarching theory of a book.
This was weak, sub-Gladwell, smug pop science. Not recommended.
This was weak, sub-Gladwell, smug pop science. Not recommended.
Conclusion: Dare to look at new unusual datasources the internet has to offer!
Very interesting data and eye opening use of new sources. This book inspired me to investigate google trends and data on my own.
Very interesting data and eye opening use of new sources. This book inspired me to investigate google trends and data on my own.
I loved this book. It is definitely in my top 5 books of 2019, I cannot recommend it enough. I read some of the other goodread reviews and no one else seemed to have as good a time as me, so take this review with a grain of salt i guess.
Basically this book is giving you tangible data about how google probably knows you better than most of your friends and family. I don't really want to spoil much as I truly recommend the read! The data he provided was super interesting to me and proves how much you can gleam from internet searches. Topics covered range from voter turnout, election results, sexual preferences, methods of speech, sports and some other topics I'm sure I'm forgetting.
As always with data scientist, they don't seem to worry too much about the ethics of what they're doing, the author covered ethical questions in a mere 10 pages but I get that that's not the point he's trying to make so I'll give him a pass. The author is successfully explains how the social sciences will be turning more and more to data rather than surveys or small experiments when you can get access to pools and pools of data from Facebook, Google and Pornhub. He goes into what makes good research a bit (what to do with huge amounts of data etc) - if that's what you're after its quite sparse in terms of how to actually conduct good research but the results he shared were fascinating.
Also it's an easy read! Read it in 4 days, it's the holidays what do you have to lose!
PS. Appaz lots of people don't finish non fiction books?? By his standard fewer than 10% make it to reading the conclusion (he was looking at economics books but still) ?? Wild times man
Nice book with lots of stories of Big Data applications (mostly: Google searches).
4 powers of Big Data (p53-54)
1. New data sets
2. Honest (no social pressures such as in surveys)
3. Ability to zoom in on subgroups
4. Causal experiments (A/B tests)
Bartleby syndrome (from Melville story, p66) “I prefer not to”
P65-70 best predictor of race horse success: size of left ventricle of heart, followed by spleen size (larger is better)
P71 “In the predictive business, you just need to know that something works, not why”
P92 Berger & Milkman: positive NYT articles get shared MORE https://www.nytimes.com/2010/02/09/science/09tier.html
P97 US newspaper tilt left (liberal bias), but just as much as newspaper readers tilt left; ie papers provide what readers want
P128 “Men make as much searches for ways to perform oral sex on themselves as they do how to give a woman an orgasm.”
P178-179 filling out earnings of $9000 as self-employed with 1 kid maximizes government tax credit; done between 2%-30% across US, driven by high concentrations of tax advisors and other people doing it. Chetty et al AER:
https://www.aeaweb.org/articles?id=10.1257/aer.103.7.2683
P259-260 some words predict defaults on p2p loans; “someone who mentions God was 2.2 times more likely to default”
When Words Sweat: Written Words Can Predict Loan Default
https://www8.gsb.columbia.edu/researcharchive/articles/15033
P283 work by Jordan Ellenburg; 90% of readers finish Tartt’s The Goldfinch, only 7% Thinking, fast and slow.
4 powers of Big Data (p53-54)
1. New data sets
2. Honest (no social pressures such as in surveys)
3. Ability to zoom in on subgroups
4. Causal experiments (A/B tests)
Bartleby syndrome (from Melville story, p66) “I prefer not to”
P65-70 best predictor of race horse success: size of left ventricle of heart, followed by spleen size (larger is better)
P71 “In the predictive business, you just need to know that something works, not why”
P92 Berger & Milkman: positive NYT articles get shared MORE https://www.nytimes.com/2010/02/09/science/09tier.html
P97 US newspaper tilt left (liberal bias), but just as much as newspaper readers tilt left; ie papers provide what readers want
P128 “Men make as much searches for ways to perform oral sex on themselves as they do how to give a woman an orgasm.”
P178-179 filling out earnings of $9000 as self-employed with 1 kid maximizes government tax credit; done between 2%-30% across US, driven by high concentrations of tax advisors and other people doing it. Chetty et al AER:
https://www.aeaweb.org/articles?id=10.1257/aer.103.7.2683
P259-260 some words predict defaults on p2p loans; “someone who mentions God was 2.2 times more likely to default”
When Words Sweat: Written Words Can Predict Loan Default
https://www8.gsb.columbia.edu/researcharchive/articles/15033
P283 work by Jordan Ellenburg; 90% of readers finish Tartt’s The Goldfinch, only 7% Thinking, fast and slow.