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Link - KEYWORD SEARCH RESULTS
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2 - PRIMARY Keyword matches for LINK LIBRARY
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Cellular Automata Resources
Complexity and Complex Systems Resources
Cybernetics and System Dynamics
Fractal Resources
Fuzzy Logic Resources
Neural Network Resources
Nonlinearity & Chaos Resources
Self-Organizing Systems Resources
Related Philosophy Resources
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The "edge of chaos" is a critical state between order and chaos in which nonlinear systems (e.g., interacting teacher and students) are at their optimum performance potential or maximum adaptability. Systems poised at the edge of chaos are maximally adaptive because of the complex connections and distinctions of their interacting agents. This complexity implies that the interacting agents are distinct enough to permit flexibility and yet connected enough to establish stability. Highly ordered assemblages such as crystals lack complexity because they have rigidly connected molecules without flexibly distinct movement. On the other extreme, highly chaotic assemblages such as gases also lack complexity because they have flexibly distinct molecules without structured connections. However, interacting agents on the edge of chaos such as students and a teacher are complex because they are distinct enough to permit flexible change and yet connected enough to establish stability. Furthermore, they can generate a holistic system of interaction that is emergent and not reducible to the individual agents. In other words, the whole is more than the sum of the parts.
Complexity may be further defined as "the ability to switch between different modes of behavior as the environmental conditions are varied" (Prigogine & Nicolis, , p. - ). Complex systems on the edge of chaos permit a flexible openness and sensitivity to varied options, which enable these systems to continually find and select the most attractive options of adjusting, replacing, or reorganizing at a higher level of fitness. However complex systems, which are either rigidly bound by ordered conditions (fused connections) or indiscriminately scattered by chaotic conditions (confused distinctions), are not able to continually adapt to higher levels of fitness (complexity).
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2 - SECONDARY Keyword matches for CHAOS AND COMPLEXITY
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Social network analysis [SNA] is the mapping and measuring of relationships and flows between people, groups, organizations, computers or other information/knowledge processing entities. The nodes in the network are the people and groups while the links show relationships or flows between the nodes. SNA provides both a visual and a mathematical analysis of human relationships. Management consultants use this methodology with their business clients and call it Organizational Network Analysis [ONA ...
Degrees
Betweenness
Closeness
Boundary Spanners
Peripheral Players
Network Centralization
Other Network Metrics
. Structural Equivalence - determine which nodes play similar roles in the network
. Cluster Analysis - find cliques and other densely connected clusters
. Structural Holes - find areas of no connection between nodes that could be used for advantage or opportunity
. E/I Ratio - find which groups in the network are open or closed to others
. Small Worlds - find node clustering, and short path lengths, that are common in networks exhibiting highly efficient small-world behavior
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What is Social Network Analysis?
Social network analysis is based on an assumption of the importance of relationships among interacting units. The social network perspective encompasses theories, models, and applications that are expressed in terms of relational concepts or processes. Along with growing interest and increased use of network analysis has come a consensus about the central principles underlying the network perspective. In addition to the use of relational concepts, we note the following as being important:
* Actors and their actions are viewed as interdependent rather than independent, autonomous units
* Relational ties (linkages) between actors are channels for transfer or ãflowä of resources (either material or nonmaterial)
* Network models focusing on individuals view the network structural environment as providing opportunities for or constraints on individual action
* Network models conceptualize structure (social, economic, political, and so forth) as lasting patterns of relations among actors
The unit of analysis in network analysis is not the individual, but an entity consisting of a collection of individuals and the linkages among them. Network methods focus on dyads (two actors and their ties), triads (three actors and their ties), or larger systems (subgroups of individuals, or entire networks.
Network theory is sympathetic with systems theory and complexity theory. Social networks is also characterized by a distinctive methodology encompassing techniques for collecting data, statistical analysis, visual representation, etc.
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