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Small world experiment

Small world experiment
The "six degrees of separation" model The small-world experiment comprised several experiments conducted by Stanley Milgram and other researchers examining the average path length for social networks of people in the United States. The research was groundbreaking in that it suggested that human society is a small-world-type network characterized by short path-lengths. The experiments are often associated with the phrase "six degrees of separation", although Milgram did not use this term himself. Historical context of the small-world problem[edit] Mathematician Manfred Kochen and political scientist Ithiel de Sola Pool wrote a mathematical manuscript, "Contacts and Influences", while working at the University of Paris in the early 1950s, during a time when Milgram visited and collaborated in their research. Milgram's experiment was conceived in an era when a number of independent threads were converging on the idea that the world is becoming increasingly interconnected. Results[edit]

http://en.wikipedia.org/wiki/Small-world_experiment

Related:  Network ScienceSocial Networking & MediaPsychologyreseau et math de la collaboration

Math algorithm tracks crime, rumours, epidemics to source (Phys.org) -- A team of EPFL scientists has developed an algorithm that can identify the source of an epidemic or information circulating within a network, a method that could also be used to help with criminal investigations. Investigators are well aware of how difficult it is to trace an unlawful act to its source. The job was arguably easier with old, Mafia-style criminal organizations, as their hierarchical structures more or less resembled predictable family trees. Beyond Facebook: The Rise Of Interest-Based Social Networks Editor’s Note: This guest post is written by Jay Jamison, a Partner at BlueRun Ventures, who focuses on early stage mobile, consumer and enterprise investments. He also serves on the boards of AppCentral, AppRedeem, Foodspotting, and Thumb. You can follow Jay on Twitter @jay_jamison or read his blog at www.jayjamison.com.

Milgram experiment The experimenter (E) orders the teacher (T), the subject of the experiment, to give what the latter believes are painful electric shocks to a learner (L), who is actually an actor and confederate. The subject believes that for each wrong answer, the learner was receiving actual electric shocks, though in reality there were no such punishments. Being separated from the subject, the confederate set up a tape recorder integrated with the electro-shock generator, which played pre-recorded sounds for each shock level.[1] The experiments began in July 1961, three months after the start of the trial of German Nazi war criminal Adolf Eichmann in Jerusalem. Milgram devised his psychological study to answer the popular question at that particular time: "Could it be that Eichmann and his million accomplices in the Holocaust were just following orders? Could we call them all accomplices?"

Entrecard, The Droppers How To : Lobo Links Blog This sort of feel like it will be a long post, but I really don’t want you skimming. I took the time to write this because I have found a system that works for me and that grants a share. Since the addition of the Entrebar the Entrecard system has become very user-friendly and it opened up some big doors for constant droppers. I warn you this is not the easy way, but the rewarding type of how to. I hope you enjoy it.

Stanford prison experiment The Stanford prison experiment (SPE) was a study of the psychological effects of becoming a prisoner or prison guard. The experiment was conducted at Stanford University from August 14–20, 1971, by a team of researchers led by psychology professor Philip Zimbardo.[1] It was funded by the US Office of Naval Research[2] and was of interest to both the US Navy and Marine Corps as an investigation into the causes of conflict between military guards and prisoners. Goals and methods[edit] Zimbardo and his team aimed to test the hypothesis that the inherent personality traits of prisoners and guards are the chief cause of abusive behavior in prison.

Équilibre de Nash - Wikipedia, l'encyclopédie libre In game theory, the Nash equilibrium is a solution concept of a non-cooperative game involving two or more players, in which each player is assumed to know the equilibrium strategies of the other players, and no player has anything to gain by changing only their own strategy.[1] If each player has chosen a strategy and no player can benefit by changing strategies while the other players keep theirs unchanged, then the current set of strategy choices and the corresponding payoffs constitutes a Nash equilibrium. The reality of the Nash equilibrium of a game can be tested using experimental economics method. Stated simply, Amy and Will are in Nash equilibrium if Amy is making the best decision she can, taking into account Will's decision while Will's decision remains unchanged, and Will is making the best decision he can, taking into account Amy's decision while Amy's decision remains unchanged. Applications[edit]

New research to uncover nuances of networks Feb. 20, 2013 9:01 a.m. When a species disappears from a region, the rest of the ecosystem may flourish or collapse, depending on the role that species played. When a storm rolls across the coast, the power grid might reconfigure itself quickly or leave cities dark for days. A snowstorm might mean business as usual in a hardy city and a severe food shortage in another, depending on the distribution strategies of residents. Each of these systems is a kind of network, with thousands of members and relationships linking them. Understanding how networks behave is key to ensuring their functioning.

Is the 90-9-1 Rule for Online Community Engagement Dead? [Data] Is the 90-9-1 Rule for Online Community Engagement Dead? [Data] Posted by Paul Schneider on Thu, Aug 11, 2011 @ 09:43 AM There is a rule that has floated around in the social media world for quite some time called the Rule of Participation Inequality or the 90-9-1 Rule. This rule states:

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