Collective phenomena in economy and society

“ We have technology, finally, that for the first time in human history allows people to really maintain rich connections with much larger numbers of people. ~Pierre Omidyar ”

Group 3 is the best

Collective Phenomena Spiders try to collectively connect with their neighbors over a larger network. Would this make the overall system stronger or weaker? Physics Names Mass Action Collective Behavior Artificial Chemistry Society Economy Blah Society Blah

Also known as mass action, collective behavior, and artificial chemistry, collective phenomena is the tendency for a lot of small individuals (like atoms or molecules) to altogether have sudden and dramatic changes of behavior by imitating their neighbors.

Strong interactions such as those in macroscopic systems frequently induce transitions and lead to new equilibrium phases of matter. These phases exhibit their own characteristic fluctuations, elementary excitations known as collective modes. Although a description of these phenomena at the microscopic level can be quite complicated, the longtime hydrodynamic behavior in the grand scheme of things often quite simple to describe. It's comparable to the collective phenomena that happens among people in the economy and society.

1. Mass action (sociology): a term for situations in which a large number of people behave simultaneously in similar ways individually and randomly, without coordination
2. Mass action (statistical physics): the proposition that a large number of small units acting randomly may compose a larger pattern

Physics

Phenomenal approaches based on this concept have led to certain quantum as well as classical field theories that over recent years have played a major role in shaping our understanding of condensed matter and high energy physics.

Critical Phenomena

Topological Phase Transitions

• condensation of vapor into liquid droplets

Quantum Fields

• Ising Model
• Solitons
• Perturbation theory in quantum mechanics
• The quantization of magnetic flux in a superconductor
• quantum Hall effect are both collective phenomena associated with thermodynamically large numbers of particles.

Economy

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Civilization, the Formation of Nations

8000 years ago, the ancestors of humanity--whether they lived in sedentary villages or mobile bands, whether they collected wild foods or herded flocks or cultivated gardens--lived in a world of kin and ritual in which the exploitation of many by a few was held in check. In a millennium or less, first in Mesopotamia, then in Egypt, then in India, China, Peru, Mexico, and elsewhere, villagers were incorporated into larger polities focused on sprawling urban centers and ruled by emergent elites. Did people willingly give up their independence to join such new polities or were they coerced by despots? The Dynamics of Civilizations Group at SFI, led by SFI External Professors Henry Wright and Doug White , and Science Board Member Bob Adams , aims to explain this fundamental transformation in the human career accelerated during the 20th century.

Languages

As time passes, languages change. Vocabulary items (and grammatical features) are passed along from care-givers to children, often with alterations of meaning and/or pronunciation. This process of “vertical” transmission may be contrasted with the “horizontal” process of borrowing features from neighboring languages. A language evolves into “daughter” languages descended by vertical transmission from a common “proto-language,” with sound changes tending to follow definite rules. Meanwhile, borrowing occurs as well, complicating the picture.

Society

Society shows sometimes abrupt changes - revolutions - which are related to phase transitions: both are sudden and dramatic changes of behavior.

Social systems are prominent examples of complex systems. Concepts, tools and models aiming at identifying generic mechanisms underlying collective phenomena in these systems are developed with the use of

Game Theory

Game theory attempts to mathematically capture behavior in strategic situations, in which an individual's success in making choices depends on the choices of others.

Gene-Culture Co-evolutionary Models

Also known as Dual Inheritance Theory(DIT), it is how human behavior is a product of two different and interacting evolutionary processes: genetic evolution and cultural evolution. DIT is a "middle-ground" between much of social science, which views culture as the primary cause of human behavioral variation, and human sociobiology and evolutionary psychology which view culture as an insignificant by-product of genetic selection.

Behavioral Experiments

War Time Sexual Violence

Sexual violence varies in extent and form among civil wars as well as inter‑state wars, among ethnic wars as well as non‑ethnic, and among secessionist conflicts. Despite the challenges to gathering data on this sensitive topic, the variation does not appear to be a product of inadequately reported violence: there are well-documented cases at the low end of the spectrum of sexual violence as well as the high end. Through multi-sited field research and new analysis of existing data, research on sexual violence at SFI, led by SFI Professor Libby Wood seeks to explain the variation in sexual violence during war. Goals include (a) documenting variation in wartime sexual violence, with particular attention to cases with little sexual violence; (b) exploring in greater depth cases where the pattern of sexual violence appears to be of particular interest in accounting for that variation; (c) developing candidate explanations for the observed variation; and (d) to the extent feasible, assessing their empirical plausibility. This project analyzes the puzzle of variation of sexual violence in the context not just of war but also in light of the cultural norms and practices of particular societies, bearing in mind that war can radically change norms and practices and that small group dynamics can profoundly undermine both individual norms and armed group policy.

Statistical Physics

Partition Function Given a thermodynamically large system that is in constant thermal contact with the environment, where both the volume $V$ and the number of constituent particles $\eta$ are fixed. $\eta$ ($\eta$ = 1, 2, 3, ...) are the exact states (microstates) that the system can occupy, generally, these can be regarded as discrete quantum states of the system.

Therefore, the canonical partition function is defined as:

$Z=\sum _{n}^{\infty }e^{-\beta E_{n}}\;$

where

$Z\;$ = statistical function of Temperature

$e\;$ = base of the natural logarithm

$\beta ={\tfrac {1}{k_{B}T}}\;$ = the inverse temperature where $k_{B}$ is the Boltzmann const

$E_{n}\;$ = total energy of the system

$n\;$ = the number of particles.

Agent Based Models

Agent-based modeling offers a useful theoretical portal from which to explore complex adaptive systems. This type of bottom-up modeling begins by capturing, in the form of simple algorithms, the essential behavior of the key agents in the system under investigation. These computations are then allowed to interact with one another, resulting in a new model system that can be explored. Agent-based models are well suited for the analysis of dynamical systems of heterogeneous, adaptive agents. These types of systems are often difficult to capture using more traditional modeling tools like axiomatic mathematics. Over the last two decades agent-based models have become an important tool in a variety of fields, and have been used to explore problems ranging from urban segregation to the flocking of birds to trading in markets. SFI External Professors George Gumerman and Tim Kohler and others are simulating ancient societies of the southwest, SFI Professor Steve Lansing is modeling the relation between rule based marriage and genetic relatedness in Bali, and SFI External Professors John Miller and Scott Page are modeling complex adaptive social systems using thoughtful agents.

Complex Networks Theory

In the context of network theory, a complex network is a network (graph) with non-trivial topological features—features that do not occur in simple networks such as lattices or random graphs. The study of complex networks is a young and active area of scientific research inspired largely by the empirical study of real-world networks such as computer networks and social networks.

Revolution

cultural conflicts and problems of social consensus are examples of phenomena being addressed.

Other Examples

Animal Magnetism, like Herding

References

1. http://www.santafe.edu/research/topics-dynamics-human-behavior-institutions.php
2. Soft Condensed Matter, by Richard A. L. Jones (Oxford University Press, 2007).
3. Solid State Physics, by J. R. Hook and H. E. Hall (Wiley, 2007).
4. http://www.tcm.phy.cam.ac.uk/~bds10/phase.html