Dynamical Systems in Social Psychology

By: Robin R. Vallacher, Andrzej Nowak

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Hardcover | 11 January 1994

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Hardcover
305 Pages

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23.57 x 15.75 x 1.96

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A dynamical system refers to a set of elements that interact in complex, often nonlinear ways to form coherent patterns. Because of the complexity of these interactions, the system as a whole may evolve over time in seemingly unpredictable ways as new patterns of behavior emerge. This metatheory has proven useful in understanding diverse phenomena in meteorology, population biology, statistical mechanics, economics, and cosmology. The book demonstrates how the dynamical systems perspective can be applied to theory construction and research in social psychology, and in doing so, provides fresh insight into such complex phenomena as interpersonal behavior, social relations, attitudes, and social cognition.

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"Vallacher and Nowak's Dynamical Systems in Social Psychology presents an attempt at overcoming the ambivalent relationship between theory and phenomena that has haunted psychology for so long. The collection of essays addresses the problems of social psychology in particular, but much of what the authors are saying applies easily to other fields in psychology... Probably for the first time in social psychology, Vallacher and Nowak have brought together a number of authors who try to establish a link between the concepts and tools of dynamic systems on the one hand and the problems, data, and theories of social psychology on the other... The book, probably the first of its kind, provides a very interesting, accessible and informative introduction to a new and exciting approach to social psychology." --PAUL VAN GEERT, University of Groningen, The Netherlands, in SCIENCE

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Non-Fiction Psychology Social Psychology Sociology & Anthropology Sociology Social Research & Statistics Medicine Medicine in General Health Systems & Services Mental Health Services

Contributors	p. xiii
Preface	p. xv
The Chaos in Social Psychology
Introduction	p. 1
The State of Social Psychology	p. 2
Theories, Issues, and Topics	p. 2
Causation and Prediction	p. 4
Boilerplate Excuses	p. 5
The Dynamics of Social Psychology	p. 7
Complexity	p. 8
Time	p. 9
Dynamical Social Psychology	p. 11
Minitheory and Metatheory	p. 13
References	p. 15
Dynamical Systems: A Tool for Social Psychology?
Introduction	p. 17
Dynamical Systems	p. 18
Dynamical Systems and Social Psychology	p. 19
Dynamical Systems: Basic Concepts and Definitions	p. 20
Dynamical Variables	p. 20
Order Parameters	p. 20
Phase Space	p. 20
Discrete Maps	p. 21
Control Parameters	p. 22
Example: Logistic Map	p. 22
Continuous Time Models	p. 23
Predator-Prey Model	p. 24
Patterns of Behavior of Dynamical Systems	p. 25
Conservative and Dissipative Systems	p. 25
Attractors	p. 25
Deterministic Chaos	p. 30
Strange Attractors	p. 30
Sensitivity to Initial Conditions	p. 30
Mixing	p. 34
Fractal Nature of Strange Attractors	p. 34
Chaos in the Real World	p. 35
Patterns of Change in Behavior	p. 35
Changes of Behavior--Bifurcations	p. 35
Bistability and Multistability	p. 39
Hysteresis	p. 40
Roads to Chaos	p. 41
Transitions in the Presence of Noise	p. 42
Signatures of Nonlinear Behavior	p. 42
Autocorrelation and Cross-Correlation Function	p. 43
Fourier Analysis	p. 43
Distinguishing Deterministic from Random Chaos	p. 45
Conclusion	p. 51
References	p. 51
The New Statistical Dynamics: An Informal Look at Invariant Measures of Psychological Time Series
Statistical Properties of Nonlinear Dynamical Systems	p. 55
The Decorrelation, Relaxation Time, [tau]	p. 58
The Dispersion and Mixing Rate, [lambda]	p. 59
Generating Dynamical Complexities, H[subscript T] and H[subscript M]	p. 62
Nonuniformity, [characters not reproducible] in Complexity Generation	p. 64
Is There a Single Dynamical Invariant Measure?	p. 66
References	p. 67
New Mathematical Techniques for Pattern Recognition
Introduction	p. 71
Linear or Nonlinear?	p. 73
On Fourier Analysis	p. 80
Coherent State Analysis	p. 86
Neural Networks	p. 91
Summary	p. 92
References	p. 92
Aggression, Love, Conformity, and Other Social Psychological Catastrophes
Canonical/Normal Social Psychology	p. 96
Smoothness/Proportionality	p. 96
Unimodality	p. 96
Catastrophe Theory: A Model That Goes Beyond the Canonical	p. 98
The Cusp Catastrophe	p. 99
The Conflict between Personal Dispositions and Social Pressure: Toward a Psychological Model	p. 102
The Elephant and the Blind Men	p. 103
Hysteresis	p. 104
A Test of the Model	p. 105
The Conformity Pilot	p. 105
Initial Conformity/Nonconformity	p. 106
Disposition to Conform	p. 106
Results	p. 106
Recapitulation	p. 108
References	p. 108
Local and Global Dynamics of Social Relations
Introduction	p. 111
Basic Concepts	p. 112
The Dynamics of Physical Systems	p. 112
The Dynamics of Biological Systems	p. 113
Linking Systems: Coordination	p. 114
Attractor Dynamics	p. 118
Order and Control Parameters	p. 119
Extension to Social Psychology	p. 121
Modeling Close Relations	p. 121
The Moreland and Levine Group Socialization Model as a Dynamical System	p. 129
Concluding Comments	p. 136
References	p. 137
The Perception and Coupling of Behavior Waves
Introduction	p. 139
Dynamical Systems as Metaphor or Theory	p. 142
Behavior Is a Wave	p. 144
Segmentation of Ongoing Behavior	p. 144
Measuring Ongoing Behavior	p. 145
Spectral Analysis of Ongoing Behavior	p. 149
Perception of Behavior Waves	p. 152
The Nature of Behavior Waves	p. 153
The Concept of Information Flow	p. 154
The Coupling of Behavior Waves	p. 156
Back to the Future	p. 165
References	p. 166
A Family of Autocorrelation Graph Equivalence Classes on Symbolic Dynamics as Models of Individual Differences in Human Behavioral Style
Introduction	p. 169
Equivalence as a Higher Order Observable	p. 170
Kinds of Dynamical Equivalence	p. 172
Experimental Data	p. 174
Behavioral Style in Experimental Tasks	p. 174
Partition of Human Behavior as Support for Equivalence Relations	p. 176
Mapping of Subject Data to the Model	p. 177
The Autocorrelation Graph (Autocorrelogram)	p. 177
The Model	p. 178
Creation of Surrogate Data	p. 181
The Tent Map	p. 181
Symbolic Dynamics on Two Letters	p. 183
Orbits as [lambda] Expansions	p. 185
Assigning Parities and Creating a[subscript l]s	p. 187
Obtaining a [lambda] Value for a Subject	p. 188
Mapping and Modeling the Surrogate Data	p. 188
Results	p. 189
Correspondence of Subject and Surrogate Models by Task	p. 189
Line Fast-Return Task	p. 189
Line Slow-Return Task	p. 190
Triangle Task	p. 191
Discussion	p. 193
References	p. 195
Toward a Dynamic Conception of Attitude Consistency and Change
Some Traditions in Attitude Research	p. 198
Attitude Measurement	p. 198
Multiple Dimensions	p. 198
Attitude Change	p. 199
Attitude Organization	p. 199
Attitudes and Behavior	p. 201
Patterns of Attitudes	p. 202
Attitude Space	p. 203
Mental Geography	p. 204
Curves and Contours	p. 206
Dynamics and Attractors	p. 207
Stability and Instability	p. 208
Attitudes as Attractors	p. 210
A Connectionist View of Attitudes	p. 211
Neural Networks	p. 211
Connectionism and Dynamical Systems	p. 213
Conclusions	p. 215
References	p. 217
Attitudes as Catastrophes: From Dimensions to Categories with Increasing Involvement
Introduction	p. 219
Two Conceptions of Individual Attitudes	p. 220
Attitudes as Points (or Regions) on a Dimension	p. 221
Implication of the Dimensional View	p. 221
Attitudes as Categories	p. 225
Implications of the Categorical View	p. 226
So Which Is It--Dimensions or Categories?	p. 227
Attitude Changes as Catastrophes	p. 227
Attitude Distributions Indicate the Nature of Attitudes	p. 230
Data Set 1: A Classic Study of the Distribution of Attitudes	p. 230
Data Set 2: A Modern Study of the Distribution of Attitudes	p. 232
Summary of Results from Both Classic and Modern Studies	p. 236
Other Implications of the Idea That Attitudes Are Catastrophic	p. 237
Implications for How to Study Attitudes	p. 238
Why Does Involvement Lead to Categorization?	p. 239
Internal Processing	p. 239
External Pressure	p. 241
Decisions and Behavior	p. 241
Why Does It Matter? Implications for Group Dynamics	p. 242
The Traditional View--Convergence	p. 242
The New View--Clustering	p. 242
Feedback of Group Outcomes to Individual Processes	p. 245
When Convergence? When Clustering?	p. 245
Individual Attitudes and the Group Mind	p. 246
References	p. 247
The Stream of Social Judgment
Introduction	p. 251
Intrinsic Dynamics	p. 253
Order Parameters	p. 253
Structure and Dynamics	p. 254
Measuring the Stream of Social Judgment	p. 257
The Problems with Self-Report	p. 257
The Mouse Paradigm	p. 258
Variation in Intrinsic Dynamics	p. 260
Temporal Patterns in Judgment	p. 260
Dynamics and Information	p. 265
Rethinking Social Thinking	p. 269
Implications for Theory	p. 269
Implications for Research	p. 272
Conclusions	p. 274
References	p. 275
Toward a Dynamical Social Psychology
Introduction	p. 279
Implications for Philosophy of the Social Sciences	p. 280
Determinism	p. 280
Causal Laws	p. 281
Unpredictability of Human Behavior	p. 282
Implications for Theory in Social Sciences	p. 283
What to Identify and Measure	p. 283
"Ambitious" Models versus Qualitative Understanding	p. 285
Qualitative Models in Social Psychology	p. 286
Complexity of Theory	p. 288
Implications for Statistics	p. 288
Nonlinear Relations	p. 288
The Danger of Averaging	p. 289
Summing Up: Social Psychology Reconsidered	p. 290
References	p. 292
Index	p. 295
Table of Contents provided by Syndetics. All Rights Reserved.

Dynamical Systems in Social Psychology

At a Glance

Hardcover

Industry Reviews

Shipping

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Defective items

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