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659 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
659 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
challenging
funny
informative
reflective
medium-paced
There were a lot of different interesting details about what people usually Google and how they react to certain things, how Big Data can help with analytics in various fields, but when I got to the middle of the book it became a bit repetitive.
Overall this is a really good listen. Does a good job illustrating the value of Big Data. A bit obsessed with Google and porn, but does an admirable job exploring other opportunities for analysis. Doppelganger discussion is particularly well done. Misses on some aspects of Surveillance issues but at least addresses some of them.
A bit depressing at times but also really interesting
medium-paced
This is a lot of self serving, thinks he can solve every problem BS. It also references Freakonomics quite a few times, glossing over some of the major issues with it. There's weird sexist jokes and a huge emphasis on sex and race in general in an uncomfortable way. Do not recommend
informative
reflective
fast-paced
Everybody Lies is an enthusiastic defence of the premise that "big data" -- such as aggregate data from the kind of things people search in Google -- might tell us things about humans that we wouldn't admit even on an anonymous survey, and which things like implicit association tests hope to dig out. My main feeling going in was that I'd expect such a dataset to have its own drawbacks, and that I'd be very sceptical if the author pretended that it did not.
Well, though the author writes enthusiastically and persuasively about the subject, he does mention some cautionary tales and drawbacks, and he makes very good points about things like sexuality. Someone in the closet in a homophobic country doesn't have much incentive to admit to being gay to an anonymous survey, but they might still search for gay porn (and indeed searches for gay porn match reasonably well across the world, showing that there's a background rate of people who are at least interested in it in principle.
(His data actually just shows where men are interested in men having sex with men, not where men are gay, which is something he doesn't really notice. Bisexual men don't exist for the purposes of his discussion here, even though he'd be much better to just talk about same-sex attraction and include the possibility of both homosexuality and bisexuality.)
The book is full of interesting examples and applications, and a sprinkling of the author's personality (as many pop-sci type books do). He's excited about his work, but not too credulous, and it's a reasonable introduction to the concept that has me... okay, not convinced that data science is actually necessarily going to produce the next great specialist in every subject (as he suggests), but hopeful that data from Google searches and other similar bodies of data can indeed teach us things about ourselves.
Well, though the author writes enthusiastically and persuasively about the subject, he does mention some cautionary tales and drawbacks, and he makes very good points about things like sexuality. Someone in the closet in a homophobic country doesn't have much incentive to admit to being gay to an anonymous survey, but they might still search for gay porn (and indeed searches for gay porn match reasonably well across the world, showing that there's a background rate of people who are at least interested in it in principle.
(His data actually just shows where men are interested in men having sex with men, not where men are gay, which is something he doesn't really notice. Bisexual men don't exist for the purposes of his discussion here, even though he'd be much better to just talk about same-sex attraction and include the possibility of both homosexuality and bisexuality.)
The book is full of interesting examples and applications, and a sprinkling of the author's personality (as many pop-sci type books do). He's excited about his work, but not too credulous, and it's a reasonable introduction to the concept that has me... okay, not convinced that data science is actually necessarily going to produce the next great specialist in every subject (as he suggests), but hopeful that data from Google searches and other similar bodies of data can indeed teach us things about ourselves.
This is a really interesting look at some of the new and interesting things that can be found by analyzing the massive amounts of data that people so freely share online in our day and age. Which is not to say that I fully trust or believe everything the author claims to be able to accomplish here. I think there is some inherent 'unknowability' when you are relying on anonymous or scrubbed search data as your primary source. Still, a lot of what is presented here is very interesting and intriguing.
In the conclusion Seth hopes that in writing this book he will have sparked enough interest in some readers to want them to enter the field of data and become data scientists. I was hooked after the first chapter, I'm ready, sign me up.
The fact that literally everything is data (there are people in China tracking their countries GDP by taking photos of apples in shops) is amazing and this books takes you on a journey through the positives and negatives in an accessible way.
The shocking part for me was the use of the N word, I understand the need to differentiate between whether it is the 'er' or 'a' spelling, but it isn't hard. There is no excuse, just don't use it.
The fact that literally everything is data (there are people in China tracking their countries GDP by taking photos of apples in shops) is amazing and this books takes you on a journey through the positives and negatives in an accessible way.
The shocking part for me was the use of the N word, I understand the need to differentiate between whether it is the 'er' or 'a' spelling, but it isn't hard. There is no excuse, just don't use it.
challenging
informative
inspiring
fast-paced