In this course, attendees will learn how to use bibliometric and citation network data to answer humanities and social science research questions. With the rise of Big Data and computational methods the humanities and social sciences are able to use innovative methods to study new research questions. Using citation data scholars can study the emergence of new academic disciplines, the emergence of new technologies, cultural narratives, and innovation among other topics. No programming knowledge or technical experience is required for this course.
For participants with no prior experience, the free session "Visualization Tools for Science of Science Queries" may help lay the groundwork for this session. Find the recording in the LYRASIS Learning Library at https://learning.lyrasis.org/
At the end of this session, participants will:
Understand the types of research questions that can be answered with citation data
Describe the basics of the python programming language and working with large data sets in a cloud computing environment
Name the types of statistical and computational methods that are used to study citation data
Enhance their skills working with large citation data
Ethan Fridmanski is the Data Services Librarian at Indiana University Bloomington Libraries. Ethan assists faculty and students with data at all phases in the data lifecycle. His services consist of instructional workshops, one on one data and methods consultations, as well as assistance with IU's data repositories such as DataCORE. In addition to his work in the Libraries, Ethan also works on the CADRE project as a member of the Technical Advisory Board and works on education and outreach to the broader CADRE community.
Ethan is an expert with a variety of programming languages and statistical software such as R, Python, SQL, and STATA among others. He has methodological expertise in a variety of computational methods including time series, survey methods, and network analysis.