Information of all kinds is now being produced, collected, and analyzed at unprecedented speed, breadth, depth, and scale. The capacity to collect and analyze massive data sets has already transformed fields such as biology, astronomy, and physics, but the social sciences have been comparatively slower to adapt, and the path forward is less certain. In this blog we look at the benefits of using data science methods in social science research.
The big data revolution offers huge potential for social scientists. However, the successful collection and rigorous analysis of this data require new skills, new collaborations, new research methods, and new computational tools. Learning new data science methods seems like a mammoth task, but there are many reasons why learning to program will benefit both you and your field of study:
Even though it takes some time at first, learning how to program can save you an enormous amount of time doing basic tasks that you would otherwise do by hand, once you get the hang of it.
Some things are impossible, or nearly impossible, to do by hand. Computers open the door for new tools and methods, but many require programming skills.
The Internet holds a wealth of data waiting to be analyzed! Whether it's collecting Twitter data, working with the Congress API, or scraping websites, programming knowledge is a must.
(Quality) programming can open the door to better transparency, reproducibility, and collaboration in the Social Sciences.
SAGE Campus presents a collection of courses to help you learn the data science skills you need to work with big data, with confidence. We have the following courses starting soon:
This blog post includes extracts from the SAGE white paper, “Who is Doing Computational Social Science? Trends in Big Data Research” and Introduction to Applied Data Science Methods for Social Scientists.