I liked this book enough to fantasize about being a data scientist for an hour. Then I had other fantasies and had to go watch videos on the internet. Speaking of which, I assumed "what the internet can tell us about who we really are" would be all creepy sex stuff (which is why I read the book). This is a fair part of the book, but there is other interesting stuff too; interesting stuff about health, sports, family violence, and how we present our lives on social media vs the awful shit we google about ourselves and our loved ones. I am convinced by the author's main point that "big data" can provide far better evidence in many cases than the dubious surveys and interviews that social scientists often rely on, even if I was not entirely convinced by all of his examples. And now that I know my searches might be used as evidence in social science studies I will feel compelled to google important issues more regularly.

3.5. Fun and interesting.
informative medium-paced

Not very cohesive, jumped around between unrelated data.
informative reflective slow-paced

Lots of politics and information is based in United States. Still, it had interesting data.
challenging funny informative reflective medium-paced
funny hopeful informative inspiring fast-paced

My favorite economics book I think about it all the time

Great to the very last page. Yes I finished it Seth.

I liked this book. It was all good until the conclusion where he rambles on about how hard it is to finish a book and how he's not getting laid and god knows what else. Then throws out some statistics about how an insignificant number of readers actually finish a book, so why bother editing this shit. Way to condescend to your audience, while at the same time neglecting them. So how's this: Fuck you, Seth Stephens-Davidowitz. I hope you never get laid.

Full title: Everybody Lies: Big Data, New Data, and What the Internet Can Tell Us About Who We Really Are. Stephens Davidowitz is a data scientist with a PhD in economics from Harvard and having worked at google. The big data he uses is largely from google, Facebook, and Pornhub. It’s easy these to days to get informations on likes and searches, and much, much more. There is so much data that is so easy to access, presumably in many cases more honest thatn self-reported data and easy to use for randomised A/B trials. Much of what he uncovers is surprising (Obama’s speech well received by pundits and the press seeking to minimise hate crimes and speech, actually inflamed racists as shown by the number of race hate searches immediately after the speech, for example) Other findings were much less surprising (how often you have sex is overreported). It mines the data to discover how important race was as a factor in both the Obama and Trump elections. He clearly and carefully explains the difference between correlation and causation and how difficult it can be to determine which you are dealing with. Stephens Davidowitz shows how valuable using such big data can be, while admitting that the data set is not necessarily perfect (how many searches have you made motivated by idle curiosity rather than a genuine search for answers?) but given the sheer amount of data is confident of his results. An interesting read, sometimes amusing, sometimes deeply serious.