
The Chaos Machine: The Inside Story of How Social Media Rewired Our Minds and Our World
by Max Fisher
4.5 stars from 1,049 reviews. Top 90% of Nonfiction books we track.
Last checked: Jun 26, 2026
While not the biggest discount we've seen for this book, it's still a great deal and we recommend grabbing it before price returns to its normal range.
Price range: $2.99 – $14.99
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Fans of these authors will like this...
- Shoshana Zuboff
- Tristan Harris
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Fans of these books will like this...
- The Age of Surveillance Capitalism
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Perfect for you if...
- You worry that social media is making the world angrier and more fractured, and want to understand exactly how and why.
- You're interested in technology criticism that's grounded in reporting rather than hand-wringing.
- You want to know what Silicon Valley insiders have said about the systems they built.
Maybe not for you if...
- You're looking for practical tips on how to use social media better or protect yourself online.
- You prefer solutions-focused books over deep dives into problems.
- You don't have patience for books that connect dots between algorithmic design and real-world violence.
About this book
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We track price drops, sale patterns, and predict when this book will go on offer next.
Price History
Kindle price over time. Green zones = periods when the book was free.
Price has dropped 13 times over the last 5 years. Goes on sale roughly every 103 days. Typically stays discounted for 6 days.
Sales Rank
Amazon sales rank: lower number = better selling book. #1 is the bestseller.
Currently around #196K in the Kindle store — a niche title.
Rating & Reviews
Purple line = star rating over time. Blue area = total review count growth.
Currently 4.5★ from 1,049 reviews
Gaining approximately 18 new reviews per month. Rating has remained stable at 4.4 over the tracking period.
Sale Prediction
Actual Predicted
This book goes on sale roughly every 103 days. Next drop estimated in about 9 weeks. Typical discount: 80% off.
Prices shown in USD from Amazon US. We continuously pull new data to improve tracking. If dates look old, it usually means there has been no significant change since the last data point.
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