Penn Libraries Presents (Angelica Rivera): on AI and Topic Modeling of Research Methods in Scientific Articles

Angelica Rivera, Bollinger Fellow in Library Innovation, will talk with us about her work with Topic Modeling of Research Methods in Scientific Articles.

"Can we use machine learning to text mine articles to identify and track statistical methods across disciplines to help students acquire useful knowledge about methods; researchers to find collaborators; and help librarians to sharpen the focus of research and pedagogical supports? Although journal articles often have keywords which are author or reader-assigned, the keywords may not include statistical methods used and rather focus on discipline-relevant topics. Angelica’s project focuses on developing 1) a machine learning pipeline to automatically assign statistical and computational methods labels to scientific research articles and 2) tools for students, researchers, and subject librarians to navigate and make sense of the associated bibliometric information. Come learn about the framework behind the label assignment and let us know what information you would like to see included in the tool production phase.

Please RSVP to attend in-person or to receive a Zoom link for the talk. We look forward to see you there!

If you are interested in presenting at one of our Wednesday at 12:00 events, please fill out the Penn Libraries Presents form.