
AI in Social Sciences Research
Routledge (Publisher)
Will be published approx. on 3. July 2026
166 pages
E-Book
978-1-040-96081-3 (ISBN)
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Description
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AI in Social Sciences Research explains how artificial intelligence (AI) is reshaping social inquiry, from data collection and research design through analysis, interpretation, and theory-building. Treating AI as both a tool kit and a methodological shift, the volume offers a clear route into machine learning (ML), natural language processing (NLP), simulation, and generative AI (GAI) for social researchers while keeping ethics, bias, transparency, and interpretability in view.
Designed for postgraduate students, early-career researchers, and instructors teaching digital and computational social science (CSS) methods, the book supports readers who want to use AI with methodological care, not just technical speed.
Designed for postgraduate students, early-career researchers, and instructors teaching digital and computational social science (CSS) methods, the book supports readers who want to use AI with methodological care, not just technical speed.
More details
Series
Language
English
Place of publication
London
United Kingdom
Publishing group
Taylor & Francis Ltd
Target group
College/higher education
Professional and scholarly
Product notice
Reflowable
ISBN-13
978-1-040-96081-3 (9781040960813)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Other editions
Additional editions

Lukasz Sulkowski | Marcin Lis | Sabina Ratajczak
AI in Social Sciences Research
Book
approx. 07/2026
1st Edition
Routledge
€52.50
Not yet published

Lukasz Sulkowski | Marcin Lis | Sabina Ratajczak
AI in Social Sciences Research
Book
approx. 07/2026
1st Edition
Routledge
€191.50
Not yet published
Persons
Lukasz Sulkowski is a professor of economic sciences and humanities specializing in higher education management, social science methodology, HRM, and organizational culture, and serves as President of WSB University.
Sabina Ratajczak is Vice-Rector for Development at WSB University, specializing in educational technologies and education management, with a particular focus on the integration of innovative digital tools into teaching and learning processes.
Marcin Lis is Vice-Rector for Student Affairs and External Relations at WSB University and holds a PhD in engineering, his research interests include quality systems, innovation project management, and integrated management systems, with a particular focus on science - business collaboration and knowledge transfer. ]
Zdzislawa Dacko-Pikiewicz is the Rector of WSB University and holds a habilitation in management and quality sciences, her research spans reputation management, innovation, family business, competence development, and sustainability, with particular relevance to debates on organisational resilience, competitiveness, and knowledge transfer.
Sabina Ratajczak is Vice-Rector for Development at WSB University, specializing in educational technologies and education management, with a particular focus on the integration of innovative digital tools into teaching and learning processes.
Marcin Lis is Vice-Rector for Student Affairs and External Relations at WSB University and holds a PhD in engineering, his research interests include quality systems, innovation project management, and integrated management systems, with a particular focus on science - business collaboration and knowledge transfer. ]
Zdzislawa Dacko-Pikiewicz is the Rector of WSB University and holds a habilitation in management and quality sciences, her research spans reputation management, innovation, family business, competence development, and sustainability, with particular relevance to debates on organisational resilience, competitiveness, and knowledge transfer.
Content
Introduction, 1. Introduction - AI and the Evolving Landscape of Social Science Research, 2. Machine Learning and Big Data Analytics in Social Sciences, 3. Natural Language Processing for Qualitative and Textual Data, 4. AI-Enhanced Research Design and Data Collection, 5. AI in Management and Business Research, 6. Psychology: AI-Assisted Paths to Mind and Behavior, 7. Anthropology - Digital Ethnography and Algorithmic Thick Description, 8. Sociology: Algorithmic Sociology and the Macro-Micro Bridge, 9. Conclusion, 10. References
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