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kil3yp 's review for:
Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us about Who We Really Are
by Seth Stephens-Davidowitz
So this book will be one of the first that I DNF'd in under 50 pages, but am still giving 2 stars to.
I'm giving it 2 stars because I think Stephens-Davidowitz is probably right; search data is a gold mine into the human psyche, and far more telling than anything we will admit to on a survey.
But I don't think Stephens-Davidowitz gave any respect to his readers' knowledge of statistical analysis, or scientific processes in general. He finds a set of data, but it doesn't support his theory. So he finds another set of data, but that also doesn't support his theory. And so he continues until he finds some shred of evidence that his theory may have some plausibility, but then immediately weights it higher than all other data. Because it obviously, is the best piece. He also confuses relationships between cause and effect items, making leaps and assumptions no paper could ever get away with.
And that's the truth about this book: it was a paper he couldn't get peer reviewed. So instead he turned it into a book to sell to the masses. Because nothing says screw you like making money on the paper your peers wouldn't support.
I'm sure there's some great tidbits in here. And I hope that there are thousands of people currently working on search data as the next big insight. But this isn't where I want to start with it. All of this being said...I won't judge if you do.
I'm giving it 2 stars because I think Stephens-Davidowitz is probably right; search data is a gold mine into the human psyche, and far more telling than anything we will admit to on a survey.
But I don't think Stephens-Davidowitz gave any respect to his readers' knowledge of statistical analysis, or scientific processes in general. He finds a set of data, but it doesn't support his theory. So he finds another set of data, but that also doesn't support his theory. And so he continues until he finds some shred of evidence that his theory may have some plausibility, but then immediately weights it higher than all other data. Because it obviously, is the best piece. He also confuses relationships between cause and effect items, making leaps and assumptions no paper could ever get away with.
And that's the truth about this book: it was a paper he couldn't get peer reviewed. So instead he turned it into a book to sell to the masses. Because nothing says screw you like making money on the paper your peers wouldn't support.
I'm sure there's some great tidbits in here. And I hope that there are thousands of people currently working on search data as the next big insight. But this isn't where I want to start with it. All of this being said...I won't judge if you do.