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jimbowen0306's review against another edition
3.0
Hmmm... This is an interesting book. It looks at what is generally called "big data" and tries to correlate it to certain outcomes like keywords in Google searches to support for Donald Trump. The argument for using this data is that people are going to be more likely to tell the truth to something that isn't real (their computer), rather than a real life person, especially when it's embarrassing when they are unsure about something.
This issue I had with the book is that it started with a bang, and went down hill from there. The author argued he wanted the book to speak to people like Freakonomics did 10yrs ago, and I can see why he thinks that. Freakonomics, however, was just more interesting. I rather suspect that if he could have chapters that gripped you like that book did then I might have enjoyed the book better. It's just after the first changer or two, it got old fast.
This issue I had with the book is that it started with a bang, and went down hill from there. The author argued he wanted the book to speak to people like Freakonomics did 10yrs ago, and I can see why he thinks that. Freakonomics, however, was just more interesting. I rather suspect that if he could have chapters that gripped you like that book did then I might have enjoyed the book better. It's just after the first changer or two, it got old fast.
bookph1le's review against another edition
3.0
Good, but also thin. I was surprised to have reached the end of the book so quickly. He does present a lot of interesting nuggets of data, but I would have liked to have seen more depth with them. Also, some of what he presents doesn't require data science. Had he talked to a feminist scholar or read a few articles by feminists, he wouldn't have been at all shocked when his data reflected a common hang-up that women share--I definitely wasn't surprised by that tidbit.
I think one of the most interesting aspects of big data is its potential to help in medicine and in social areas. The author makes a convincing argument for the ways big data can be a valuable diagnostic tool for doctors, and how it could help identify patients who show early warning signs of various diseases. I also think big data has the potential to help police and social workers more effectively identify specific geographic areas of concern as far as potential crimes go, though I also share the author's worries about how far this could be taken.
All in all, it's a good read, entertaining and often surprising. As I said, I would just like to have seen some more depth.
I think one of the most interesting aspects of big data is its potential to help in medicine and in social areas. The author makes a convincing argument for the ways big data can be a valuable diagnostic tool for doctors, and how it could help identify patients who show early warning signs of various diseases. I also think big data has the potential to help police and social workers more effectively identify specific geographic areas of concern as far as potential crimes go, though I also share the author's worries about how far this could be taken.
All in all, it's a good read, entertaining and often surprising. As I said, I would just like to have seen some more depth.
patiolinguist's review against another edition
2.0
2.5* Some interesting data science applications but, overall, too many words and not enough cohesion.
ellenclibrarian's review against another edition
3.0
This book is fascinating, depressing, and informative. It is at its best when he is not discussing the biggest data, but explaining correlation and causation, and the importance of creativity in the questions we ask of data. The biggest data, what we actually enter in Google search boxes, is a sad disclosure of the human condition- maybe. Point off for his disparaging library comments; point back for quoting Kundera in regard to data analysis.
meaghanjohns's review against another edition
3.0
"The days of structured, clean, simple, survey-based data are over. In this new age, the messy traces we leave as we go through life are becoming the primary source of data."
This book was useful as a broad, high-level survey of big data for someone who has not been previously introduced to the fied. The author also puts forward his thesis that we can learn more about people through their Google searches rather than through their answers in interviews or on surveys, since they are more likely to be raw and honest in their searches.
I didn't particularly enjoy the author's style of writing or attempts at humour, but I do feel that I'm now more informed about the power of big data and how it might be used than I was before reading Everybody Lies.
This book was useful as a broad, high-level survey of big data for someone who has not been previously introduced to the fied. The author also puts forward his thesis that we can learn more about people through their Google searches rather than through their answers in interviews or on surveys, since they are more likely to be raw and honest in their searches.
I didn't particularly enjoy the author's style of writing or attempts at humour, but I do feel that I'm now more informed about the power of big data and how it might be used than I was before reading Everybody Lies.