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If you've wondered how on earth the USA became so polarized, so violent, racist and ignorant, you've got to read this book. Everybody Lies makes it clear that all this meanness and hatred was always there but people kept it a secret. We learn the truth about infidelity, violence, sexuality, etc. etc. Eye-opening and completely fascinating.
Great book with many fascinating insights based on real data and data science. The author explains his approach to data science very well. If you liked Freakonomics, you'll love this book.
An entertaining and informative read. Stephens-Davidowitz clearly describes how Big Data combined with intuitive searches reveals surprising information.
Amazing book, Taught me about Data Science, using most googled words, the beginning and the next up and coming field of discipline
This book was OK, but not great. The basic premise is that people do not answer surveys honestly; they answer in a way that makes themselves look good. Also, traditional surveys have relatively small samples.
On the other hand, if you can analyze millions of Google searches, you can get loads more data, and people are apparently more honest in their Google searches than they are in surveys.
I have to say that my reaction to that was “Don’t Google anything you would not want on the front page of the Seattle Times (or your newspaper of choice)!” This author was looking at aggregate anonymous data, but clearly Google knows what you have Googled as an individual. Talk about scary!
There were some interesting tidbits. For example, the author notes (in hindsight, of course) that the big data of Google searches showed that the current president was likely to win in 2016, even if people were unwilling to admit they would vote for him when surveyed. Also, people claim they plan to vote, but they don’t Google things like “how to vote” and “where to vote”, which demonstrates they were just trying to look good to the person taking the survey.
Some areas of the country appear to have relatively few gay people, but Google searches from those parts of the country indicate otherwise.
People say on Facebook that they like the Atlantic more than the National Enquirer. Their Google searches and clicks indicate otherwise. Whatever your Facebook friends are saying on Facebook is probably untrue, as people are trying to make themselves look more impressive to others. (If you did not already know that, you are gullible.)
I was underwhelmed by this book. It might make an interesting magazine article, but it does not have enough substance for a book.
Just some guy's opinion wrapped up in a pseudoscientific evaluation of Google searches. You can't just observe something and then draw a bunch of conclusions about it. It might be mildly interesting for a conversation starter, but it is too low in actual usable information to be of help to anyone. I do agree with him in that everybody lies. I just don't agree that he has chosen the most interesting reason for why they do it.
(And he seems to have more than a fair share of Trump Derangement Syndrome)
The Google search box is the new confessional box for a digital age. A place where deepest fears and forbidden wishes find new, unfiltered expression. In this new confessional, we don’t seek salvation— we seek information. And the questions we ask it often reveal things about us that were previously hidden, or misunderstood.
Subtitled, “Big data, new data, and what the internet can tell us about who we really are,” this book was written by a former Google data scientist who uses “confessional” search data on a vast scale to draw new insight into the human condition. It’s a fascinating and compelling work which kept me reading from cover to cover in one day.
I could quibble with the author’s overconfidence in the power of internet search data to accurately depict people’s true selves, because I believe that our relationship with the digital world is fundamentally a charade, and will one day come to be seen as such. But for now, the newness and sheer volume of this new form of data is electrifying and groundbreaking, and has great potential to shed new light on the previously dark corners of the human psyche. I eagerly look forward to the author’s planned sequel in which he intends to dive deeper into the “small data” that lives between the topline trends.
The ancient Romans had a saying about a mountain giving birth to a mouse. I thought of this as I listened to the audiobook of Seth Stephens-Davidowitz’s “Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are.” Stephens-Davidowitz makes great claims for the valuable insights that can be gleamed from the enormous data contained in digital sources such as Google searches and social media postings. Alas, his own insights thus gleamed lean toward the underwhelming. To give just one example, he goes to great lengths to finally answer the vexing question of whether professional basketball players tend to come from economically disadvantaged backgrounds. (Spoiler: they don’t.) His conclusions are meaningful, no doubt, but not comparable, say, to the germ theory of disease. Still, his book is always interesting in a “Freakonomics” sort of way, and well worth the reader’s time.
If it wasn't for the fact that this book is the February read for my job's book club, I probably would've never read it; but I am so glad that I did! I couldn't even pull something from it to quote in this review because I felt like there were whole paragraphs that I wanted to share.
Everybody Lies is both informative and fascinating. I feel like Seth Stephens-Davidowitz did a great job explaining the significance and revolutionary impact of data on our world. His thesis didn't surprise me; however, many of the findings that he shared in his book did. And based on everything Seth discussed in Everybody Lies, it's crystal clear that data science is real and it's impact on our lives is big.
Interesting and surprising insights into the meaning of what we English-speakers search for when we search on the Internets.
For example, "One theory I am working on: Big Data just confirms everything the late Leonard Cohen ever said." (82n)
Also, why did the author not bother sweating the book's conclusion, and go for beers with friends instead? You'll need to read the book to find out (but remember, the author's premise is that unless it's big anonymous data, everybody lies).
A quick, coherent read, told thoughtfully and with humour.
How disappointing this book turned out to be and I had to stop reading after page six when the author posited post election racism search results from Google. There is great promise in big data and it has certainly provided us with heretofore unknown insights. However, one has to be careful and inquisitive about results and findings. Correlation does not always prove causation. While the author is a data scientist, making blanket statements and not being curious or delving deeper into the results is a disservice to the field and readers.
Reminded me in some ways of Malcolm Gladwell books. Some of the stories are very unique, like the one about the guy who figured out how to tell if a horse would be a winning race horse or not. Some readers may find other topics less interesting. Towards the end he mentions a website that could be the start of some really useful medical research at PatientsLikeMe.com. Individuals can register there, contact others with similar health problems, keep records, and even participate in research projects.
"Google searches are the most important data set ever collected on the human psyche." The author, an economist and former Google data scientist, begins from this premise and examines the way that data analysis can reveal more about humanity than our answers to surveys (and certainly more than our self-conscious and image-conscious Facebook posts). As one telling example, Stephens-Davidowitz shows that Americans use the n-word in Google searches at an alarming rate (despite both polls and conventional wisdom about race relations), and that this behavior is spread equally across both political parties and across Eastern states. Parents ask Google twice as often if a daughter is overweight than a son (despite more overweight boys in the population); Google searches potentially also reveal data about sexual behaviors and hang-ups, about suicide rates, and about cannabis use.
Methodologically speaking, the author seems to place too much trust on pornography site searches as evidence of sexual tastes across humanity, but his overall introduction to "big data" analysis for social questions is strong and easy for the layperson to follow.
"Everybody Lies" by Seth Stephens-Davidowitz is not just a provocative title. Granted that is what lured me to pick it up but the introduction and very first chapter, "Your faulty Gut," hooked me. Seth is a data scientist to the core and he talks passionately about his craft or should i say Art? The premise of the book is that all humans lie or twist the truth in such a way as to make themselves look better - unless they are surfing the internet. It is these clicks that data scientists study to find truths. Perhaps the area were we lie the most is about our sexuality and our sexual proclivities. Thus the author spends a good bit of his chapter "Digital Truth Serum" examining this area and comes out with surprising realities. As the author states in his acknowledgement a professor asked him what his mother thought of the work he did; because of his work on taboo subjects. However, his mother taught him that he should follow his curiosity no matter where it led.
Stephens-Davidowitz compared the number of people who read the beginning of a book to those who read the end. Well, Seth I read not only your conclusion but your acknowledgement too. And yes, if the sequel comes out, "Everybody 'still' lies," you have one confirmed reader.
This book explains in a very interesting way how BIG DATA from internet could be analyzed and thus utilized in various domains in our lives (health, politics, education, sexuality, history... you name it!).
First an important distinction in the truth value between data collected from social media sites (e.g. Facebook) and data from search engines (e.g. Google search). So if according to the author "Facebook is digital brag-to-my-friends-about-how-good-my-life-is", it can not be a reliable source of who we really are. On the other hand analyzing what people search in Google is more truthful. An illustrative funny example: the top word wives associate with 'husbands' in FB is 'the best' 'my best friend' while in google search it is 'gay' 'a jerk'!
So, what makes BIG DATA from Internet so useful and unique to understand human social interactions (versus classical research such as surveys)?
First, it is more true (e.g. does racism really does not matter in political choices in America?).
Second, because of its great volume it can allow us to delve into very specific subsets of geography or segment. For example by analyzing the searching of some key symptoms we can know that en epidemic is occurring somewhere, or we can know the sexual preference of middle age women living in rural areas.
Third, it allows for experimentation in a very fast and cheap way (the A/B experiments obviously done on us everyday by Google and FB).
Fourth, it allows us to look at new data we would have never thought to seek with regular research (for example or when the US became a truly united country as to when it was referee to as the United State is not are!).
The book is loaded with interesting examples to illustrate the points and it is fun to read. It is also touching on the ethical implications of this revolution in data science.
It concludes with a BIG DATA analysis of the percentage of people who would finish a book (only 3% for a serious book like Capital in the 21st Century or 7% for Thinking, Fast and Slow, while more than 90% for a novel like Goldfinch!).
This is a very important book to understand the World we are living in now, and how are data scientists utilizing the information we post and type everyday in the Internet!
a digital revolution as internet activity provides reliable data to analyse; what could possibly go wrong here
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.
Full review: https://shayshortt.com/2017/07/13/everybody-lies/
Interesting, though it tends toward the sensational. I'm also skeptical about generalizing about sexuality based on internet porn site data.
The information about human thoughts and behaviour revealed in this book is fascinating. Equally fascinating is the methodology used to gather the information, primarily millions of anonymized Google searches analyzed by geography, by frequency, by time, by choices. These are deemed to reveal "true thoughts” through real action vs what people tell you in person or in surveys. Common held views about human behaviour and even our intuition about what motivates people are proving wrong. One example: the change in on-line searches during and following two different President Obama speeches appealing for tolerance after a terrorist attack in the U.S. As with any new technology the ramifications can be both positive and negative. Finding “doppelgängers” - people who are statistically similar to you - could provide life-saving medical information or the means to manipulate you. The opportunities for social sciences - economics, sociology, and psychology - are significant; no longer will a small sample of paid students provide supposedly meaningful information about human behaviour through controlled experiments. Analysis of data for causal connections (e.g. socio-economic backgrounds of NBA players) also has power. But does Big Data like Google searches really reveal true human behaviour? Maybe sometimes. I think more work needs to be done on this point.
I'm very torn about this book. On the one hand, it's an accessible and engaging introduction to the uses of big data. On the other hand, I suspect that the vast majority of people who want to read a book about the uses of big data want something that goes deeper than an accessible introduction; that, along with the author's somewhat bro-ish tone, was my main frustration. But if you're hoping for an easily digestible look at a potentially confusing topic, "Everybody Lies" could be a solid match for you!