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Ivancevic_Applied-Diff-Geom

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602 <strong>Applied</strong> <strong>Diff</strong>erential <strong>Geom</strong>etry: A Modern IntroductionAfα ❘ FB∨✒g ❅❅❅❅❅❅❅❘G ◦ FG(F (A))LIFEG(F (f))∨G(F (g))F (f)✲❘F (A)F (α)F (B)∨ ✒F (g) G✠ ❘G(F (α))G(F (B))✒Af✲ f(A)❅ MATTERg ◦ f ❅ ❅ g ❅❘ ✠g(f(A))4.9.8 <strong>Geom</strong>etrodynamics of Human CrowdIn this subsection we formulate crowd representation model as an emotion–field induced collective behavior of individual autonomous agents [<strong>Ivancevic</strong>and Snoswell (2000)].It is well–known that crowd behavior is more influenced by collectiveemotion than by cognition. Recall from previous subsection that accordingto Lewinian psychodynamics, human behavior is largely determined byunderlying forces (needs). For him, a force–field is defined as ‘the totalityof coexisting motivational facts which are conceived of as mutually interdependent’[Lewin (1997)]. He also stresses psychological direction andvelocity of behavior.On the other hand, a number of factor–analysis based studies showthat human emotion is not a single quantity, but rather a multidimensionalspace. For example, in [Skiffington (1998)], authors assessed emotions withsingle adjective descriptors using standard linear factor analysis, by examiningsemantic as well as cognitive, motivational, and intensity features ofemotions. The focus was on seven negative emotions common to severalemotion typologies: anger, fear, sadness, shame, pity, jealousy, and contempt.For each of these emotions, seven items were generated correspond-

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