Big Data and Social Science: Data Science Methods and Tools for Research and Practice

Description

• Explains how big data is changing social science research
• Shows how to design a full data-intensive research or policy study
• Introduces modern data sources such as web data, APIs, and large databases
• Explains data collection, cleaning, and data management clearly
• Covers text data, network data, and large-scale social datasets
• Introduces modeling, machine learning, and computational analysis
• Explains data visualization for social science findings
• Discusses data quality, bias, and limitations of big data
• Emphasizes ethics, privacy, and responsible data use
• Uses real examples to connect theory with practice

Who Should Read This Book

• Social science researchers in sociology, economics, and political science
• Public policy researchers working with large datasets
• Graduate students (MA, MSc, PhD) learning computational social science
• Early-career researchers moving from traditional to data-driven research
• Data scientists working on social or policy problems
• Statisticians collaborating with social scientists
• Government analysts and policy professionals
• NGO and development sector researchers
• Readers with limited programming background who want practical guidance

Key Strengths & Importance

• Provides a complete workflow from data collection to analysis and reporting
• Clearly connects data science tools with social science questions
• Covers modern methods like machine learning and network analysis
• Explains complex ideas in an accessible, beginner-friendly way
• Focuses strongly on ethical and privacy concerns
• Addresses bias, fairness, and data quality issues
• Encourages responsible and transparent research practices
• Uses real-world case studies and examples
• Supports interdisciplinary research across fields
• Helps researchers generate evidence-based social insights