Algorithmic identification of Ph.D. thesis-related publications
A proof-of-concept study
Bibliographic Data
| ID | 21443399 |
|---|---|
| Authors | Paul Donner (0000-0001-5737-8483, German Centre for Higher Education Research and Science Studies, corresponding author) |
| Year | 2022 |
| Volume | 127 |
| Issue | 10 |
| Pages | 5863-5877 |
| Publication date | 2022-10-01 |
| Open Access | Yes |
| Type | ARTICLE |
| Venue | Scientometrics (JOURNAL) |
| Journal identifiers | ISSN: 0138-9130 • E-ISSN: 1588-2861 |
| Publisher | Springer Science and Business Media LLC (PUBLISHER) |
| DOI | 10.1007/s11192-022-04480-w |
| OpenAlex | W4292409480 |
| Language | EN |
| Citations received | 1 |
| References cited | 12 |
In this study we propose and evaluate a method to automatically identify the journal publications that are related to a Ph.D. thesis using bibliographical data of both items. We build a manually curated ground truth dataset from German cumulative doctoral theses that explicitly list the included publications, which we match with records in the Scopus database. We then test supervised classification methods on the task of identifying the correct associated publications among high numbers of potential candidates using features of the thesis and publication records. The results indicate that this approach results in good match quality in general and with the best results attained by the “random forest” classification algorithm
Data mining · Data science · German · Identification (biology) · Information retrieval · MEDLINE · Quality (philosophy) · Random forest · Scopus · Task (project management) · Artificial Intelligence · Biomedical Text Mining and Ontologies · Computer Science · Research Data Management Practices · scientometrics and bibliometrics research
Modern Applied Statistics with S
On the shoulders of students? The contribution of PhD students to the advancement of knowledge
Bias in random forest variable importance measures
Citation analysis of Ph.D. theses with data from Scopus and Google Books
Comparing institutional-level bibliometric research performance indicator values based on different affiliation disambiguation systems
Identifying constitutive articles of cumulative dissertation theses by bilingual text similarity. Evaluation of similarity methods on a new short text task
| Citations per year | 0.5 |
|---|---|
| Citation span | 2024 - 2024 (1) |
| Highly cited | No |