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The Cambridge handbook of behavioural data science / edited by Ganna Pogrebna, Thomas T. Hills
- Format:
- Book
- Series:
- Cambridge handbooks in psychology
- Language:
- English
- Subjects (All):
- Human behavior.
- human behavior.
- Physical Description:
- 1 online resource
- Other Title:
- Cambridge handbook of behavioral data science
- Handbook of behavioural data science
- Behavioural data science
- Place of Publication:
- Cambridge : Cambridge University Press, 2026
- Summary:
- "The Cambridge Handbook of Behavioural Data Science offers an essential exploration of how behavioural science and data science converge to study, predict, and explain human, algorithmic, and systemic behaviours. Bringing together scholars from psychology, economics, computer science, engineering, and philosophy, the Handbook presents interdisciplinary perspectives on emerging methods, ethical dilemmas, and real-world applications. Organised into modular parts-Human Behaviour, Algorithmic Behaviour, Systems and Culture, and Applications—it provides readers with a comprehensive, flexible map of the field. Covering topics from cognitive modelling to explainable AI, and from social network analysis to ethics of large language models, the Handbook reflects on both technical innovations and the societal impact of behavioural data, and reinforces concepts in online supplementary materials and videos. The book is an indispensable resource for researchers, students, practitioners, and policymakers who seek to engage critically and constructively with behavioural data in an increasingly digital and algorithmically mediated world"-- Cambridge Core
- Contents:
- Introduction : how to read this book / Ganna Pogrebna and Thomas T. Hills
- History of behavioural data science : successes and challenges / Ganna Pogrebna and Thomas T. Hills
- Overview of behavioural data science / Ganna Pogrebna
- Behavioural data science : framework and topology of methods / Ganna Pogrebna
- Behavioural data science for understanding human decisions, choices and judgement / Ganna Pogrebna and Thomas T. Hills
- Psychological theories of decision-making under risk / Thorsten Pachur and Veronika Zilker
- Prediction-oriented behavioural research and its relationship to classical decision research / Ori Plonsky and Ido Erev
- The ABCs of behavioural influence / Thomas T. Hills
- Word and sentence embedding methods for studying human behaviour / Ada Aka and Sudeep Bhatia
- Predictive Bayesian modelling in cognitive sciences / Joshua Ignatius
- Human aspects of AI-related risks : a behavioural data science approach / Deborah Webster and Ganna Pogrebna
- Generative AI and behavioural data science / Ganna Pogrebna
- How successful are existing algorithms in explaining and predicting human behaviour? / Alexander Kharlamov
- Emotion and big data : the elephant in the room? / Karen Renaud
- Smart bots? A behavioural approach to measure the ‘intelligence’ of conversational AI pre-ChatGPT / Marisa Tschopp, Dagmar Monett, Markus Maurer and Marc Rüef
- ChatGPT & Co : exploring conversational abilities of large language models from a behavioural perspective / Luca Gärtner, Marisa Tschopp, Teresa Windlin and Yelin Zhang
- Machine behaviour / Patrick Henz
- Modelling choice behaviour using artificial intelligence / Andreas Glöckner
- Anthropomorphic learning : hybrid modelling approaches combining decision theory and machine learning / Ganna Pogrebna
- Systems, culture and human–machine teaming / Ganna Pogrebna and Thomas T. Hills
- Cognitive networks as models of cognition and behaviour : an introduction / Massimo Stella
- Agent-based modelling in social networks / Spyros Angelopoulos
- Modelling context-dependent behaviour / Marco Del Vecchio
- A short primer on historical natural language processing / Thomas T. Hills and Alessandro Miani
- Behavioural data in complex economic and business systems / Glenn Parry
- Applications of statistical mechanics and cyber-physical systems to behaviour / Frédy Santoso
- Systems behaviour for sustainable AI / Aakanksha Jaiswal
- Systems behaviour and experimentation / Yevgen Bogodistov
- 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 / Ivan S. Maksymov
- Applications of behavioural data science / Ganna Pogrebna
- Pro-social nudging / Juliette Tobias-Webb
- Social media analytics / Rob Procter
- Quantifying luck / Chengwei Liu
- Quantifying the connection between scenic beauty and reported health using deep learning and econometrics / Chanuki Illushka Seresinhe
- Money, methodology and happiness : using big data to study causal relationships between income and well-being / Gordon D. A. Brown, Edika Quispe-Torreblanca and Jon N. Gathergood
- Human–data interaction : the case of Databox / Jon Crowcroft, Gareth Tyson and Richard Mortier
- Natural language processing in behavioural data science : using computational linguistics to understand and model behaviour / Marco Del Vecchio
- Understanding collective behaviour using online data and mobile phones / Federico Botta, Tobias Preis and Helen Susannah Moat
- Bursty events : analysing human memory over a century of events using The New York Times / Joseph L. Austerweil, Charlie Pilgrim and Kesong Cao
- Behavioural data science in financial services / Akshay Nayak and Pruthvi Taranath
- XR, VR and AR applications in behavioural data science / Toufique Soomro
- On cryptoasset traders’ behaviour / Kateryna Kononova and Anton Dek
- Behavioural data science of cybersecurity / Ganna Pogrebna and Ning Nguyen
- Behavioural data science ethics and governance pre-AI Act : from research data ethics principles to practice : data trusts as a governance tool / Sylvie Delacroix and Jessica Montgomery
- Behavioural data science ethics and governance post-AI Act : responsible approach to network and collective choice modelling / Immaculate Motsi-Omoijade
- Notes:
- Includes bibliographical references
- Online resource; title from PDF title page (Cambridge Core, viewed June 3, 2026)
- Other Format:
- Print version: Cambridge handbook of behavioural data science
- ISBN:
- 9781108939010
- 1108939015
- OCLC:
- 1579845986
- Publisher Number:
- CIPO000353363
- Access Restriction:
- Restricted for use by site license
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