Big Data and Social Science

A Practical Guide to Methods and Tools

Features

• Takes an accessible, hands-on approach to handling big data in the social sciences
• Presents all the key big data tools in a non-intimidating way to social and data scientists while not neglecting research questions and purposes
• Illustrates social science and data science principles through real-world applications
• Links computer science concepts to real social science research
• Promotes good scientific practice
• Provides data and code as well as programming exercises on GitHub

Summary

Both Traditional Students and Working Professionals Acquire the Skills to Analyze Social Problems.

Big Data and Social Science: A Practical Guide to Methods and Tools shows how to apply data science to real-world problems in both research and the practice. The book provides practical guidance on combining methods and tools from computer science, statistics, and social science. This concrete approach is illustrated throughout using an important national problem, the quantitative study of innovation.

The text draws on the expertise of prominent leaders in statistics, the social sciences, data science, and computer science to teach students how to use modern social science research principles as well as the best analytical and computational tools. It uses a real-world challenge to introduce how these tools are used to identify and capture appropriate data, apply data science models and tools to that data, and recognize and respond to data errors and limitations.