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"An introduction to network science for behavioural and social researchers. This book demonstrates network science applications in psychology, aging, creativity, memory, language evolution, belief structures, child language learning, and group problem-solving. Designed for graduate students and researchers in the cognitive sciences, behavioural economics, health and social policy"--
List of contents
Part I. A Brief Guide to Network Science: 1. Making and recognizing networks; 2. Network metrics; 3. Generative network models and network evolution; Part II. Language and Learning: 4. Zipf's law of meaning: the degree distribution of the mind; 5. Network learning: growing a lexicon by degrees; 6. What is distinctive: exploring edge types in multi-layer networks; 7. The small-world spectrum: using small worlds to compare networks; 8. The birthplace of new words: identifying node origins; 9. Agent-Based models of language emergence: structure favors the orangutan; Part III. Mental Processes: 10. False memories: spreading activation in memory networks; 11. Cognitive foraging: exploration versus exploitation in memory search; 12. Age-related Cognitive Decline: a network enrichment account; 13. Creativity: how noisy processes create novel structure; Part IV. Social Dynamics: 14. Network illusions: how structure misleads us; 15. Group problem solving: harnessing the wisdom of the crowds; 16. The Segregation of belief: how structure facilitates false consensus; 17. The conspiracy frame: coherence through self-supporting beliefs; 18. The Kennedy paradox: games of conflict and escalation; 19. Fund people not projects: a universal basic income for research; References.
About the author
Dr Thomas Hills is a Professor of Psychology at the University of Warwick. He directs the Behavioral and Data Science MSc at the University of Warwick, concentrating on how humans represent and navigate information in the mind and society. He has previously held fellowships with the Alan Turing Institute and the Royal Society.
Summary
This book demonstrates network science applications in psychology, ageing, creativity, memory, language evolution, belief structures, child language learning, and group problem-solving. Designed for graduate students and researchers in the cognitive sciences, behavioural economics, and health and social policy.
Foreword
An introduction to network science for social and behavioural researchers, with online R code and simulations.
