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Wiki at War: Conflict in a Socially Networked World

Wiki at War: Conflict in a Socially Networked World

Mad Scientists and Fighter Pilots 

Stanley Milgram shocked the world.

   He did not look like a man who would perpetrate an out- rage. No, Milgram seemed like who he was—a young profes- sor trying to wend his way up the ivory tower. With wavy hair, scratchy beard, and baggy suit, he dressed the part of a Yale University junior lecturer in social psychology. But Stanley Milgram had an obsession with the dark side.

   On June 18, 1961, the New Haven Register carried a brief ad recruiting subjects for “memory research.” The gig paid well—four dollars plus fifty cents bus fare. At the time, the minimum wage stood at $1.15 an hour. For starving students and blue- collar workers the offer seemed like found treasure.

   It did not take too long to gather a lineup interested in easy money. Under the shade of the tall trees bordering High Street, men, old and young, made their way like clockwork to Linsly- Chittenden Hall. They trudged past the weathered gray-stone frontage on Yale’s Old Campus, one an hour from six to eleven each evening, Monday to Friday.

   A gaunt man in a gray lab coat met each at the door and identified himself as “Mr. Williams.” Then Williams intro- duced volunteers to the man who would be their research partner: middle-aged, portly, smiling, apparently nervous “Mr. Wallace.”

The network 

   Networks are not new. They are as old as the universe. Networks simply define the relationships between entities whether describing a collection of galaxies or the construction of an atom. They are often illustrated by depic- tions of “hubs” and “spokes” that graphically portray how subjects are con- nected to one another.

   The recognition and study of networks became a popular subject of sci- entific research in the 1950s while Milgram was still an undergraduate at Harvard. Until recently, most research on the behavior of networks focused on the natural world. Ecologists, for example, have applied network analysis to the life sciences using mathematical models to help understand what drives large fluctuations in wildlife populations. More recently, scientists have studied the properties of small-scale networks, identifying the emer- gent properties of molecules within cells.

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