Stanley Milgram’s small-world experiment, popularly termed as the “six degrees of separation” model, claimed that two perfectly random people were typically only six connections away from each other, assuming a connection to be an acquaintance they knew by name. The threory essentially made the world seem a lot small, by proving that we were all much more interconnected in the global network than anyone ever imagined. Ever since Milgram publicized the findings of this experiment, popular culture has been enamored with his theory. Hollywood has made frequent use of the idea from the popular game of Six Degrees of Kevin Bacon, to using it as a base for the overwhelmingly opportunistc connectedness of characters on shows like Lost. These are all human networks, but the theory’s applicability does not stop there.

Wikipedia, arguably one of the most popular sources of online information, is a network of linked articles written by whoever wants to contribute preferrably unbiased information on any topic whatsoever. The author of an article can include links to other already existing articles. Articles are accessible to anyone else who wishes to edit or add to the information, or perhaps put in more links to more articles relevant to the subject. The articles are put into larger categories based on their subject matter with other articles that share relevant characteristics. Wikipedia represents an excellent example of an electronic network, where the articles represent the nodes and the links between them represent edges. Many of the principles that can be applied to social networks between people can also be applied to the network of Wikipedia articles. One such principle is the idea of Six Degrees of Separation.

The Six Degrees of Wikipedia is a tool that claims that any two articles listed on Wikipedia can be connected by six or fewer steps, assuming you’re using the full, properly disambiguated names of articles. Having tested this a number of times, including finding the number of steps between popular South African group Ladysmith Black Mambazo and the 1990s popular television show Boy Meets World , and between New Age musician Enya and classical composer Maurice Ravel, I found that articles with the most unrelated topics are in fact linked by less than six steps.  In the first search above, the links went from Boy Meets World to ABC (a relatively strong link considering that Boy Meets World was in fact aired on ABC) to Life Savers to Ladysmith Black Mambazo. There is a tiny mention of Life Savers in the article for ABC, and the connection to LBM is that they sang the Life Savers theme song a capella at some point. The connection in the second link is equally as random, with the connection between the two musicians being that both have had an asteroid named after them.

What I found to be the more interesting extension of the Six Degrees of Separation model is the fact that random links tend to be the ones that more successfully link pages together in under six steps than stronger closer links. Thinking about Wikipedia in almost geographical terms, if two articles are very closely related in topic, then they are “closer” together, whereas if two topics are completely unrelated, they are farther apart and have only random connections. In the two examples above, it took very random far reaching connections to find a path of under six steps to the target. If the search was forced to go through only close links, such as Enya having to go through New Age Music (since Enya and Maurice Ravel are both musicians) to Classical Music to Maurice Ravel, the path would get extended (although not significantly in this case).

One major difference between Milgram’s Six Degrees of Separation model and its extension to Wikipedia is that in Milgram’s experiment, random people were told to find the shortest path to a Boston stock broker by sending a letter, but they didn’t have the goal of keeping it close to 6 connections, and had no information as to how close their acquaintance was to their target. Basically, people sent letters to acquaintances they figured would be more likely to know a Boston stock broker, and potentially missed shorter but more random paths as a result. In the case of Wikipedia, we have perfect information in finding the shortest path between two articles, so this is not necessarily a perfect example of Milgram’s findings.