Introduction To Computational Tools And Techniques For Social Research

This course will provide graduate students the critical technical skills necessary to conduct research in computational social science and digital humanities, introducing them to the basic computer literacy, programming skills, and application knowledge that students need to be successful in further methods work. The course is divided into three main sections: skills, applications, and community engagement. The “skills” portion will introduce students to basic computer literacy, terminologies, and programming languages - i.e. Unix Shell, R, Python, and Git. The second part of the course provides students the opportunity to use the skills they learned in part 1 towards practical applications such as automated text analysis, geospatial analysis, data collection via APIs, and data visualization. The third section on community engagement will introduce topics such as ethics and privacy, best practices of reproducible research, scholarly communication and collaboration, and how to further one’s research using UC Berkeley campus resources. See course resources on GitHub.