Using OpenAlex to Analyse Cited Reference Patterns

Understanding what material an institution cites is an important piece of journal renewal or cancellation decisions. Many proprietary products exist that can provide this type of data but require a paid subscription to access. Therefore, this project develops an open and repeatable process to extract cited reference data using OpenAlex, a freely available database of publication metadata. The code is written in Python and publicly provided in two Jupyter Notebooks. Part 1 demonstrates how to use the OpenAlex API to extract publications which meet user-defined criteria and collect the cited references within. Part 2 provides a standardized set of graphs, data visualizations, and tables to explore and answer questions about cited reference patterns. A case study of one university is provided. Using an open dataset lets anyone run this analysis, and posting the code publicly makes the procedure reproducible, saves time, and allows for extensibility by others.