
handle: 10609/150472
Scientometrics is a field aimed at measuring and analyzing scholarly literature. It helps researchers better understand the dynamics of research fields, and it provides a comprehensive approach to the quantitative features and characteristics of science and scientific research. Some existing approaches to performing scientometrics studies are DBLP, Lens.org, Faceted or Alexandria; being DBLP the most representative in the field of computer science. However, the current analysis research relies on outdated datasets and is mainly based on ad-hoc studies that lack semantic information (e.g., explicit links between papers and authors, or between authors and conferences). To address this situation, in this project, we propose an approach to creating a relational database to facilitate the analysis of research data in computer science.
data Science, Relational databases -- TFG, DBLP, scientometrics, Bases de dades relacionals -- TFG
data Science, Relational databases -- TFG, DBLP, scientometrics, Bases de dades relacionals -- TFG
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
