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Produktbild: The Cambridge Handbook of Behavioural Data Science
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The Cambridge Handbook of Behavioural Data Science

Aus der Reihe Cambridge Handbooks in Psychology

276,99 €

inkl. gesetzl. MwSt., Versandkostenfrei

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.06.2026

Herausgeber

Ganna Pogrebna + weitere

Verlag

Cambridge Academic

Seitenzahl

834

Gewicht

500 g

Sprache

Englisch

ISBN

978-1-108-83739-2

Beschreibung

Produktdetails

Einband

Gebundene Ausgabe

Erscheinungsdatum

18.06.2026

Herausgeber

Verlag

Cambridge Academic

Seitenzahl

834

Gewicht

500 g

Sprache

Englisch

ISBN

978-1-108-83739-2

Herstelleradresse

Libri GmbH
Europaallee 1
36244 Bad Hersfeld
DE

Email: gpsr@libri.de

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  • Produktbild: The Cambridge Handbook of Behavioural Data Science

  • The Cambridge handbook of behavioural data science; Preface; List of contributors; Handbook abstract; Introduction: how to read this book; Part I. Introduction to Behavioural Data Science: 1. History of behavioural data science: successes and challenges; 2. Overview of behavioural data science; 3. Behavioural data science: framework and topology of methods; Part II. Human Behaviour: 4. Behavioural data science for understanding human decisions, choices, and judgement; 5. Psychological theories of decision making under risk; 6. Prediction oriented behavioural research and its relationship to classical decision research; 7. The ABCs of behavioural influence; 8. Word and sentence embedding methods for studying human behaviour; 9. Predictive Bayesian Modelling in cognitive sciences; 10. Human aspects of AI-related risks: a behavioural data science approach; Part III. Algorithmic Behaviour: 11. Generative AI and behavioural data science; 12. How successful are existing algorithms in explaining and predicting human behaviour?; 13. Emotion and Big Data: The Elephant in the Room?; 14. Smart Bots? A Behavioural Approach to Measure The 'Intelligence' of Conversational AI Pre-Chat GPT; 15. Chatgpt & CO - exploring conversational abilities of large language models from a behavioural perspective; 16. Machine behaviour; 17. Modelling choice behaviour using artificial intelligence; 18. anthropomorphic learning: hybrid modelling approaches combining decision theory and machine learning; Part IV. Systems and Culture: 19. Systems, culture, and human-machine teaming; 20. Cognitive networks as models of cognition and behaviour: an introduction; 21. Agent-based modelling in social networks; 22. Modelling context-dependent behaviour; 23. A short primer on historical natural language processing; 24. Behavioural data in complex economic and business systems; 25. Applications of statistical mechanics and cyber-physical systems to behaviour; 26. Systems behaviour for sustainable AI; 27. Systems behaviour and experimentation; 28. Quantum mechanics of human perception, behaviour and decision-making: a do-it-yourself model kit for modelling optical illusions and opinion formation in social networks; Part V. Applications: 29. Applications of behavioural data science; 30. Pro-social nudging; 31. Social media analytics; 32. Quantifying luck; 33. Quantifying the connection between scenic beauty and reported health using deep learning and econometrics; 34. Money, methodology, and happiness: using big data to study causal relationships between income and well-being; 35. Human-data interaction: the case of databox; 36. Natural language processing in behavioural data science: using computational linguistics to understand and model behaviour; 37. Understanding collective behaviour using online data and mobile phones; 38. Burstier events: analysing human memory over a century of events using the New York; 39. Behavioural data science in financial services; 40. XR, VR, and AR applications in behavioural data science; 41. On cryptoasset traders' behaviour; 42. Behavioural data science of cybersecurity; 43. Behavioural data science ethics and governance pre-AI act: From research data ethics principles to practice: data trusts as a governance tool; 44. Behavioural data science ethics and governance post-AI act: responsible approach to network and collective choice modelling; Part VI. Concluding Remarks: List of main abbreviations and acronyms; Glossary.