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660 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
660 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
Don't trust what people tell you, trust what people do.
I recommended this book so many times before I had even finished it. It had a similar feel to freakonomics but looking at Big Data from google and what it can tell us about ourselves. Not something I normally would have picked up but I’m really glad I did.
I will think twice before I ever google anything ever again.
This was unexpectedly enjoyable, and even laugh out loud funny at times.
The first non-fiction book I finished in less than a month, and for me, that’s a huge accomplishment.
This was unexpectedly enjoyable, and even laugh out loud funny at times.
The first non-fiction book I finished in less than a month, and for me, that’s a huge accomplishment.
challenging
informative
reflective
medium-paced
The subtitle is far more accurate than the title. What the internet can tell us about who we really are is a bit appalling. The book contained tons of pg-13+ conversations involving sex, swear words, and racist language. Most of it was fascinating, but some of it I didn't want to read in public.
A couple years ago, I read several "secret life of" type titles. I learned about the dark side of groceries, the anthropomorphic nature of trees, and the backstory of etymology and dictionaries. If I were to title this book, I think I'd call it: The Secret Life of Our Internet Searches, or something like that.
Interesting things in the book:
In the introduction alone, you are horrified by the racism revealed through google searches for the n-word. I did find it interesting that the greater divide in racism isn't north/south, but rather, east/west.
Chapter 1 had fascinating anecdotes about the predictive power of specific orders of google searches for various health symptoms. This chapter also had some interesting stats about NBA players.
Chapter 3 had interesting notes about tells for male and female romantic relationship connections as well as gender differences in words that are more often used by one gender or the other. Sentiment-analysis was also a new concept to me. Text is coded as positive or negative and tone/mood can be measured.
Chapter 4 - incentive to search for things you are not incentivized to disclose to a surveyor
Some parts of the country are better than others at giving kids a chance to escape poverty.
Students who were taught fractions via a game tested worse than those who learned fractions in a more standard way.
A couple years ago, I read several "secret life of" type titles. I learned about the dark side of groceries, the anthropomorphic nature of trees, and the backstory of etymology and dictionaries. If I were to title this book, I think I'd call it: The Secret Life of Our Internet Searches, or something like that.
Interesting things in the book:
In the introduction alone, you are horrified by the racism revealed through google searches for the n-word. I did find it interesting that the greater divide in racism isn't north/south, but rather, east/west.
Chapter 1 had fascinating anecdotes about the predictive power of specific orders of google searches for various health symptoms. This chapter also had some interesting stats about NBA players.
Chapter 3 had interesting notes about tells for male and female romantic relationship connections as well as gender differences in words that are more often used by one gender or the other. Sentiment-analysis was also a new concept to me. Text is coded as positive or negative and tone/mood can be measured.
Chapter 4 - incentive to search for things you are not incentivized to disclose to a surveyor
Some parts of the country are better than others at giving kids a chance to escape poverty.
Students who were taught fractions via a game tested worse than those who learned fractions in a more standard way.
Finally a Data Science Book that’s fun
Author does an amazing job explaining his research in a fun and intuitive way. Coming from someone with a B.S. in Data Science I can attest that this has easily been an inspiration and reread
Author does an amazing job explaining his research in a fun and intuitive way. Coming from someone with a B.S. in Data Science I can attest that this has easily been an inspiration and reread
I went into this with high expectations after hearing about it on a podcast. Alas, although the topic and some of the findings are interesting, the author really rubbed me the wrong way. Is it surprising that parents have different, gender-stereotyped expectations of their sons and daughters that come through in their Google searches? Not unless you live in a bubble (that also protects you from the wealth of products marketed toward women's insecurities about vaginal odours... another phenomenon that came as a complete surprise to Stephens-Davidowitz). This book also made me think about about ethics and informed consent--when a user downloads an app are they really consenting to participate in research? Why is that a standard imposed on academics but not businesspeople, especially when some of this research ends up published in academic journals? Particularly when it goes beyond measurement and into experimentation (cf. the big to-do when Facebook manipulated newsfeeds to mess with users' moods). I think the chapter that got me the most was the one on men Googling "how to kill your girlfriend" etc. - the takeaway message was that we don't want to go down the slippery slope of prosecuting thought crimes, but maybe it would be good to track down the potential targets and warn them someone is thinking of murdering them. Is the issue really that women aren't aware, or that they have trouble getting restraining orders, or having them enforced? Again, bubble. A few chapters in I thought this would be a 3-star read, by the end I was down to 2 stars (and yes, I did finish it). Writing this review cemented it at 1.
This book was extremely interesting and was written in a simplistic way which was always understandable. I recommend reading if you want to understand more about the human psyche as represented through our not so secret secrets.
This book presents some interesting results from an exciting field with a lot of potential. However, I think the author thinks a little too highly of his field. I think he spends too long trying to convince the reader of certain ideas about big data that are pretty obvious to everyone (at least to anyone likely to be attracted to a book about data analysis in the first place). I think most people immediately intuit the concept of using big data without a condescending encouragement that we shouldn't be intimidated by the big scary subject that the author is a master of. For example, he explains that Facebook posts/likes are not necessarily representative of reality because people sometimes (gasp) try to post things that will impress their friends. I think we all already knew that. He says that comparing the salaries of Harvard graduates with salaries of another school is not a good way to tell how much going to Harvard improves your earning potential. Again, that should be obvious to any thinking person.
Despite going to some length to elucidate these obvious potential pitfalls of data analysis, he fails to adequately address other potential shortcomings. In particular, he extols at some length the virtue of Google search data, specifically the honesty. While Google data is probably free of some systematic problems with traditional (i.e. survey & testing) data, I do not think the author adequately considers alternative motives/meanings for some of the searches he discusses. If you limit your Google searches to things in the form of a certain question (e.g. "Is my husband ________"), are you getting skewed data because a certain type of person queries in explicit questions instead of as keywords (e.g. "________ husband"). He chuckles at some personal questions people ask that Google can't possibly answer (e.g. "How tall am I") but fails to seriously discuss what rational purpose a person might have in mind when typing that.
The author seems to be an astute economist, and he is clearly introspective about some larger issues in his field. I wouldn't be surprised if he actually has a more sophisticated and nuanced view of the strengths and limitations of the data and has more rigorously considered certain seeming deficiencies in the studies that he describes. However, even if we give him the benefit of the doubt to say he thinks about them but doesn't put them in the book, that feels condescending, as if he doesn't think the reader is sophisticated enough to consider it.
Despite going to some length to elucidate these obvious potential pitfalls of data analysis, he fails to adequately address other potential shortcomings. In particular, he extols at some length the virtue of Google search data, specifically the honesty. While Google data is probably free of some systematic problems with traditional (i.e. survey & testing) data, I do not think the author adequately considers alternative motives/meanings for some of the searches he discusses. If you limit your Google searches to things in the form of a certain question (e.g. "Is my husband ________"), are you getting skewed data because a certain type of person queries in explicit questions instead of as keywords (e.g. "________ husband"). He chuckles at some personal questions people ask that Google can't possibly answer (e.g. "How tall am I") but fails to seriously discuss what rational purpose a person might have in mind when typing that.
The author seems to be an astute economist, and he is clearly introspective about some larger issues in his field. I wouldn't be surprised if he actually has a more sophisticated and nuanced view of the strengths and limitations of the data and has more rigorously considered certain seeming deficiencies in the studies that he describes. However, even if we give him the benefit of the doubt to say he thinks about them but doesn't put them in the book, that feels condescending, as if he doesn't think the reader is sophisticated enough to consider it.
What a bunch of lies LOL...kidding. But also seriously, this book causes you to question to so many facts you thought you knew. Not necessarily something I wanted to feel during the time where 'fake news' has become the thing, but it gives good reflection points to ensure you challenge yourself to ask why and what does the data really say.
For me, this shows that curiosity and the courage to question yourself and others is a good thing, as long as done ethically and with the point of understanding versus judging.
There are times you can tell a white male wrote this and as a women, there are a few eyerolls. I did appreciate though the desire to really understand and that I can relate to quite a bit.
Overall I liked this book a lot and appreciate how big data can help us but will always appreciate how any great power can be abused, and the author did not shy away from that.
For me, this shows that curiosity and the courage to question yourself and others is a good thing, as long as done ethically and with the point of understanding versus judging.
There are times you can tell a white male wrote this and as a women, there are a few eyerolls. I did appreciate though the desire to really understand and that I can relate to quite a bit.
Overall I liked this book a lot and appreciate how big data can help us but will always appreciate how any great power can be abused, and the author did not shy away from that.
informative
lighthearted
slow-paced
Narrator sounds like a robot.