Further Reading — Chapter 20: Six Degrees — How Small-World Networks Open Big Doors

Primary Sources

Milgram, Stanley. "The Small-World Problem." Psychology Today 1, no. 1 (1967): 60–67. The original accessible presentation of Milgram's small-world experiments. More readable than the technical versions and captures the spirit of the research. Note: the Psychology Today piece is where the "six degrees" concept entered popular consciousness, even though Milgram himself didn't use that phrase.

Watts, Duncan J., and Steven H. Strogatz. "Collective Dynamics of 'Small-World' Networks." Nature 393 (1998): 440–442. The foundational mathematical paper. Two pages, dense with mathematics, enormously influential. The specific model they propose — starting from a regular lattice and introducing random rewiring — is the key theoretical contribution. Freely available from many sources online.

Leskovec, Jure, and Eric Horvitz. "Planetary-Scale Views on a Large Instant-Messaging Network." In Proceedings of the 17th International Conference on World Wide Web (WWW '08), 915–924. New York: ACM, 2008. The Microsoft Messenger study. Analyzing 240 million users and 30 billion messages to find average path length of 6.6 hops. Methodologically sophisticated and clearly written. Available from ACM Digital Library.

Barabási, Albert-László, and Réka Albert. "Emergence of Scaling in Random Networks." Science 286, no. 5439 (1999): 509–512. The preferential attachment paper. Shows how power-law degree distributions arise naturally from simple growth rules. The evidence from the World Wide Web, power grids, and actor collaboration networks is compelling. The paper is short (two pages) and accessible to non-specialists.

Books for the General Reader

Watts, Duncan J. Six Degrees: The Science of a Connected Age. New York: Norton, 2003. Watts's own popular science treatment of small-world network theory, written for a general audience. Goes beyond the 1998 paper to examine how small-world structure affects epidemics, financial contagion, and social change. One of the best accessible treatments of network science.

Watts, Duncan J. Everything Is Obvious: How Common Sense Fails Us. New York: Crown Business, 2011. Watts's more recent and provocative book, examining how hindsight bias and common sense lead us to draw false lessons from network phenomena. The chapter on social epidemics revisits and complicates the Gladwell connector thesis.

Barabási, Albert-László. Linked: The New Science of Networks. New York: Perseus Publishing, 2002. Barabási's popular treatment of scale-free networks and preferential attachment. Accessible and engaging, with examples drawn from biology, economics, the internet, and social networks. The best introduction to the hub-and-spoke structure of real-world networks.

Gladwell, Malcolm. The Tipping Point: How Little Things Can Make a Big Difference. New York: Little, Brown, 2000. The source of the Connector concept. Read this for the vivid examples and accessible narrative, then read Watts's critiques for the theoretical complications. Together they provide a balanced view.

Christakis, Nicholas A., and James H. Fowler. Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives. New York: Little, Brown, 2009. A popular and research-grounded treatment of how social networks influence health, happiness, politics, and behavior. Particularly good on how properties (including luck-adjacent phenomena like obesity, smoking, happiness) spread through network ties in ways that extend several degrees beyond direct connections.

For the Technically Inclined

Kleinberg, Jon M. "Navigation in a Small World." Nature 406 (2000): 845. The paper proving that not all small-world networks are navigable — the distribution of long-range connections must follow a specific pattern for efficient decentralized routing. Short and mathematically elegant.

Dodds, Peter Sheridan, Roby Muhhamad, and Duncan J. Watts. "An Experimental Study of Search in Global Social Networks." Science 301, no. 5634 (2003): 827–829. The online replication of Milgram's experiment, using email rather than postal chains. Found similar chain lengths with higher completion rates than Milgram. Also found that successful chains relied heavily on geographic and occupational proximity as routing heuristics.

Newman, M. E. J. "The Structure and Function of Complex Networks." SIAM Review 45, no. 2 (2003): 167–256. The definitive comprehensive review of network science, covering everything from degree distributions to community structure to network robustness. Graduate-level but clearly written. The standard technical reference.

Easley, David, and Jon Kleinberg. Networks, Crowds, and Markets: Reasoning About a Highly Connected World. Cambridge: Cambridge University Press, 2010. A rigorous but accessible textbook combining economics, computer science, and sociology in the analysis of networks. Chapter 20 specifically covers the Milgram experiment and small-world models. Freely available online.

On Super-Connectors Specifically

Burt, Ronald S. "The Network Structure of Social Capital." Research in Organizational Behavior 22 (2000): 345–423. Burt's account of how structural position in networks (specifically, bridging "structural holes") generates social capital. Directly relevant to understanding why super-connectors create value — and why that value is positional, not purely personality-based. This is also the precursor to Chapter 21's treatment of structural holes.

Uzzi, Brian, and Jarrett Spiro. "Collaboration and Creativity: The Small World Problem." American Journal of Sociology 111, no. 2 (2005): 447–504. An examination of Broadway musical collaboration networks showing that small-world structure (the right mixture of clustering and bridging) predicted commercial and artistic success. The sweet spot between too much clustering (repetitive) and too much randomness (incoherent) is where the most creative and commercially successful work happened.

Cross, Rob, and Andrew Parker. The Hidden Power of Social Networks: Understanding How Work Really Gets Done in Organizations. Boston: Harvard Business Press, 2004. A practical, research-grounded treatment of how informal networks inside organizations determine who actually gets things done and who has real influence — which often differs dramatically from the organizational chart. Useful for identifying hubs within organizations.

Network Visualization Tools

NetworkX (networkx.org) The standard Python library for network analysis and visualization, used in this chapter's code example. Comprehensive documentation and tutorials available.

Gephi (gephi.org) An open-source network visualization platform. Much more powerful than NetworkX for visual exploration of large networks. Supports community detection, centrality calculation, and a wide range of layout algorithms. Free and available for Mac, Windows, and Linux.

LinkedIn InMaps LinkedIn previously offered an InMaps feature that visualized users' networks as a graph, automatically detecting clusters. The feature has been discontinued, but third-party tools (such as inmaps.org alternatives) partially replicate the functionality.

Oracle of Bacon (oracleofbacon.org) The Kevin Bacon game, implemented computationally. Calculates Bacon numbers for any actor in the Internet Movie Database (IMDb). A playful but genuinely useful demonstration of small-world network properties.

Historical and Philosophical Background

Guare, John. Six Degrees of Separation. New York: Vintage, 1990. The play that gave the "six degrees" concept its popular name. A complex, funny, and troubling exploration of social connection and disconnection. Worth reading as a humanistic counterpart to the scientific literature.

Buchanan, Mark. Nexus: Small Worlds and the Groundbreaking Science of Networks. New York: Norton, 2002. An accessible popular science book tracing the history of small-world network science from Milgram through Watts and Barabási. Good historical context and clear explanations.