A topic model approach to measuring interdisciplinarity at the National Science Foundation

• Published in: Scientometrics Vol. 100; no. 3; pp. 741 - 754
• Main Author: Nichols, Leah G.
• Format: Journal Article Conference Proceeding
• Language: English
• Published: Dordrecht Springer Netherlands 01.09.2014; Springer
• Subjects: Bibliometrics. Scientometrics; Bibliometrics. Scientometrics. Evaluation; Computer Science; Exact sciences and technology; Funding; Government agencies; Information and communication sciences; Information science. Documentation; Information Storage and Retrieval; Library and information science. General aspects; Library Science; Sciences and techniques of general use; Visualization; Interdisciplinarity; Network analysis; Topic model; Text mining; Interdisciplinary field; Scientific research
• ISSN: 0138-9130; 1588-2861
• DOI: 10.1007/s11192-014-1319-2

As the National Science Foundation (NSF) implements new cross-cutting initiatives and programs, interest in assessing the success of these experiments in fostering interdisciplinarity grows. A primary challenge in measuring interdisciplinarity is identifying and bounding the discrete disciplines that comprise interdisciplinary work. Using statistical text-mining techniques to extract topic bins, the NSF recently developed a topic map of all of their awards issued between 2000 and 2011. These new data provide a novel means for measuring interdisciplinarity by assessing the language or content of award proposals. Using the Directorate for Social, Behavioral, and Economic Sciences as a case study and drawing on the new topic model of the NSF’s awards, this paper explores new methods for quantifying interdisciplinarity in the NSF portfolio.