AI in Social Sciences Research explains how artificial intelligence is reshaping social inquiry, from data collection and research design through analysis, interpretation, and theory-building. Treating AI as both a toolkit and a methodological shift, the volume offers a clear route into machine learning, natural language processing, simulation, and generative AI for social researchers, while keeping ethics, bias, transparency, and interpretability in view.

Key features include:

· Practical guidance on integrating AI into social science research workflows, without losing theoretical and contextual judgement

· Coverage of core techniques, including machine learning for prediction and pattern discovery, and NLP for large-scale textual and qualitative data

· Discussion of explainability and “black box” risks, with approaches for interpretability and responsible use

· Cross-disciplinary examples spanning sociology, psychology, anthropology, political science, economics, and management

· A critical account of research integrity issues: data quality, bias, privacy, accountability, and the limits of automation

Designed for postgraduate students, early-career researchers, and instructors teaching digital and computational social science methods, the book supports readers who want to use AI with methodological care, not just technical speed.