Abstract
Our study compares journal citations from dissertations granted at three universities (Penn State, Cornell, and Auburn) using a novel bibliometric approach: text mining. We first tested the validity of text mining as a method for collecting journal title mentions by comparing text mining results with human-tallied results on a set of dissertations. We then text mined a group of dissertations using a preexisting list of journal titles in order to count journal title mentions in combination with the number of dissertations citing each title. The combination of journal title mentions and number of citing dissertations created a ranking for comparison across institutions. Our study presents text mining as a reliable and less time-intensive option for certain types of bibliometric analyses and also shows the utility of a ranked score approach (CD rank) for making cross-institutional citation comparisons.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1-9 |
| Number of pages | 9 |
| Journal | Serials Review |
| Volume | 49 |
| Issue number | 1-2 |
| DOIs | |
| State | Published - 2023 |
All Science Journal Classification (ASJC) codes
- Library and Information Sciences