Computational Thinking and Social Science

Whilst providing a fundamental understanding of computational social science, this book delves into the tools and techniques used to build familiarity with programming and gain context into how, why and when they are introduced. The overall focus is on helping you understand and design computational social science research, alongside delving into hands-on coding and technical instruction.

Key features include:

• Further reading
• Exercises accompanied by sample code
• Programming examples in Scratch, Python and R
• Key concepts
• Chapter summaries With experience in course design and teaching, Matti Nelimarkka has a deep understanding of learning techniques within computational social sciences, with the main aim of blending researching, thinking and designing together to gain a grounded foundation for coding, programming, methodologies and key concepts.

Auteur

Matti Nelimarkka has over a decade of experience in teaching programming: from high school students and freshmen in computer sciences to generic introduction courses for STEM and social science students. He also regularly teaches research method, both traditional and computational to students in STEM and social science, with a special focus on graduate students and advanced computational research methods. His experiences combined with research-based insights on programming education provide him a deep understanding how to make learning fruitful and effective for students.

In his scholarly work on computational social science, Dr. Nelimarkka has focused on the essential role of social science theories to structure research formulation and then pinpointing and - when necessarily - developing new tools and approaches to tease out an answer to this question. In addition, his work in the critical algorithm studies gives insights to the challenges of reliability and validity, often not sufficiently addressed in computational social science.

This book brings together his experiences across programming and conducting social science has led him to develop an approach where computational thinking and programming are blended with empirical research questions and methods and for higher level questions of doing new kind scholarly work with social science.