Small World
Mark Buchanan
Most of us have had the experience of running into a friend of a friend far away from home - and feeling that the world is somehow smaller than it should be. We usually write off such unlikely encounters as coincidence, even though it seems to happen with uncanny frequency. According to a handful of physicists at Los Alamos and other cutting-edge research labs around the world, it turns out that this small-world phenomenon is no coincidence at all. Rather, it is a manifestation of a hidden and powerful design that binds the world together. In this title, Mark Buchanan tells the story of how a stunning discovery in complexity science is revolutionizing the way we understand networks. The Internet, the brain, power-grids and the global economy are all networks that seem to have evolved a small-world geometry - with properties independent of the nature of the things themselves. The author argues that this underlying pattern may be one of nature's greatest design tricks, and the book shows us how scientists are putting this new insight to work.
Award History
0 wins · 1 total
| Award | Year | Result | Category / Notes |
|---|---|---|---|
| Royal Society Science Book PrizeMajor | 2003 | Shortlist | Secondary source |
Experimental book profileGenerated by GPT-5.4 nano · may contain inaccuracies
This is an unverified interpretation of the catalog description, offered as an opt-in discovery experiment—not as bibliographic fact.
01 Central figures
None extracted with sufficient confidence.
02 Central places
None extracted with sufficient confidence.
These suggestions did not meet the normal display threshold and are more likely to be wrong.
- Los Alamos55%
03 Suggested argument
The small-world phenomenon is not coincidence but a hidden, powerful design in network complexity that reveals shared geometry underlying systems like the Internet, brain, power grids, and the global economy.
Model confidence 68%
04 Reading orientation
45 / 100 academicTrade / academic crossover
An estimate of intended readership and scholarly apparatus—not quality or importance.
Confidence percentages are the model's own estimates. Profile confidence: 62%.