| Sumario: | Citation Analysis is a use-based methodology that provides insight and can inform librarians' collection decisions. However, citation analysis can be labor-intensive and time-consuming. In addition, it primarily focuses on traditional library materials such as books, journals, book chapters, and conference proceedings, while often overlooking materials such as datasets, software, government documents, media, performances, and so on. This study integrates artificial intelligence (AI) in the citation analysis process to label citations according to resource type so that librarians might identify what resources scholars are using and citing. In addition to describing how to integrate AI into citation analysis, the authors evaluate the methodology's success, with an overall accuracy score of 97.16 percent.
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