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662 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
662 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This is worthwhile read although findings if not the methodology will likely be outdated within 10 years. Stephens-Davidowitz tells a story for a general audience. It's pretty simple. We, in some ways and to an extent, reveal true things about ourselves in our Google queries.
Men and women ask Google about their physical and relationship insecurities. Men are often concerned with their sexual performance duration, their penis size, and whether their significant other is cheating. Women are often concerned by the smell of their vaginas and why their significant others aren't having sex with them.
Both sexes, at least in our current time period, are interested in incestual porn on PornHub and some women show an interest in rape fantasies on PornHub. Here I should mention that the author rarely uses absolute numbers, but reports rates and comparisons to the opposite sex. So, don't be overly concerned about the prevalence, but you should be aware of the existence. Especially because these are taboo subjects.
He finds that rates of out gay men seem lower than expected in certain conservative and rural parts of the country, but that the missing gay men reappear in search queries. The same goes for the supposedly non-existent gay men in Iran and Sochi, Russa. Given this data, Seth expects about 5% of men to be gay.
Kids ask Google about dealing with abusive parents, especially in the aftermath of the 2008 recession. Women in states with restricted access, ask Google about DIY abortions. Racists search for racist jokes or combine a racial category with a strong negative adjective.
Some of the story confirms our cultural understanding of how the world works. Some of our cultural stories are disconfirmed. These, of course, interest me the most.
He has some warnings against how to use big data, and this data in particular, for individuals, businesses, and governments. For example, governments should be extremely cautious about trying to use it to predict or prevent crimes by an individual for compelling statistical and ethical reasons. A good use would allocate resources to a geography area, such as gay support groups expanding their presence to certain areas or government child services to others where abuse search terms are increasing. I was fascinated that racist search terms spiked during and after a President Obama speech haranguing Americans to be more tolerant, but a later speech that simply told stories of non-white Americans as soldiers, doctors, teachers, engineers, etc was associated with many fewer racist searches.
Two obvious pitfalls to be aware of when using this data. First, these queries are not directly measuring the things we are interested in - they are proxies. So, there's risk of conflating what we can measure with the truth. Two, since predictability does not always lead to explanatory theory, we risk a host of misunderstandings, such as the cause-effect relationship or the turkey problem. The turkey problem is the Thanksgiving turkey who lives a great life and continues to belief it will live a great life until, unbeknownst to it, a certain holiday arrives on the calendar.
Men and women ask Google about their physical and relationship insecurities. Men are often concerned with their sexual performance duration, their penis size, and whether their significant other is cheating. Women are often concerned by the smell of their vaginas and why their significant others aren't having sex with them.
Both sexes, at least in our current time period, are interested in incestual porn on PornHub and some women show an interest in rape fantasies on PornHub. Here I should mention that the author rarely uses absolute numbers, but reports rates and comparisons to the opposite sex. So, don't be overly concerned about the prevalence, but you should be aware of the existence. Especially because these are taboo subjects.
He finds that rates of out gay men seem lower than expected in certain conservative and rural parts of the country, but that the missing gay men reappear in search queries. The same goes for the supposedly non-existent gay men in Iran and Sochi, Russa. Given this data, Seth expects about 5% of men to be gay.
Kids ask Google about dealing with abusive parents, especially in the aftermath of the 2008 recession. Women in states with restricted access, ask Google about DIY abortions. Racists search for racist jokes or combine a racial category with a strong negative adjective.
Some of the story confirms our cultural understanding of how the world works. Some of our cultural stories are disconfirmed. These, of course, interest me the most.
He has some warnings against how to use big data, and this data in particular, for individuals, businesses, and governments. For example, governments should be extremely cautious about trying to use it to predict or prevent crimes by an individual for compelling statistical and ethical reasons. A good use would allocate resources to a geography area, such as gay support groups expanding their presence to certain areas or government child services to others where abuse search terms are increasing. I was fascinated that racist search terms spiked during and after a President Obama speech haranguing Americans to be more tolerant, but a later speech that simply told stories of non-white Americans as soldiers, doctors, teachers, engineers, etc was associated with many fewer racist searches.
Two obvious pitfalls to be aware of when using this data. First, these queries are not directly measuring the things we are interested in - they are proxies. So, there's risk of conflating what we can measure with the truth. Two, since predictability does not always lead to explanatory theory, we risk a host of misunderstandings, such as the cause-effect relationship or the turkey problem. The turkey problem is the Thanksgiving turkey who lives a great life and continues to belief it will live a great life until, unbeknownst to it, a certain holiday arrives on the calendar.
This book is filled with interesting facts about our behaviors, but I believe it could have been summarized more effectively. It's highly likely that your experience will differ if you approach the book with a different goal in mind. However, in my experience, it was quite repetitive.
i am glad i've read this book but i thought it would open up my eyes more. i've already known a lot of information written there but still, it showed me the insides and statistics of google and big brother watching us. i've even become more conscious and careful about what i google and what i do in real life. tho a big con for me is the number of sex-assosiations. but i guess all people are animals, so they can assosiate all the hard information with something they are already familiar with?
Absolutely fascinating. I kept reading tidbits to my husband, who didn't seem to care as much, but I found nearly all of the subjects interesting and definitely new information to me. Highly recommend!
Another level of my big data fascination: I read an actual sciency book. Can't believe it.
It's such a shame I'm useless at maths because this book is basically my dream job.
It's such a shame I'm useless at maths because this book is basically my dream job.
El autor termina el libro diciendo que (spoiler) los datos confirman que la mayoría de los lectores de este tipo de libros no los terminan, así que no se va a molestar en escribir una conclusión decente. Tal cual me pareció el libro, muy interesante en los primeros capítulos pero se le fue acabando la pila al final. En cualquier caso vale la pena para introducirse al mundo del big data con ejemplos interesantes y con potencial para lucirse en conversaciones.
Not great. Seems like the author discovered Google trends and lost track of all context. First 2/3rds of the book is all about correlations with absolutely no causation. He mentions this later but many of the foundational arguments feel flawed at this point.
So this book took me forever as it was a pretty dry economics read however it was facinating. Freakonomics with more data
I never really knew anything about Big Data before picking up this book and boy did I learn a ton. The author’s writing tone is relatable, articulate and honest. I love the concept that data is all around us, especially in the social media platforms we use daily. I applaud the author, too, for recognizing and relaying to us the limitations to this type of data. Great book!
It was an interesting concept, but the book brings up an idea then meanders along in so many different paths without finishing the first thought that it is never really clear how the story ties with the Everybody Lies idea. It is probably a good introduction to anyone relatively new to big data and data extraction. There were some very intriguing points that I wish the author had fleshed out more rather than use it a bridge to the next idea.