Department of Computer Science
Permanent URI for this community
Browse
Browsing Department of Computer Science by Subject "Bibliographical citations"
Now showing 1 - 1 of 1
Results Per Page
Sort Options
- ItemUsing test data to evaluate rankings of entities in large scholarly citation networks(Stellenbosch : Stellenbosch University, 2019-04) Dunaiski, Marcel; Geldenhuys, J.; Visser, Willem; Stellenbosch University. Faculty of Science. Dept. of Mathematical Sciences. Division Computer Science.ENGLISH ABSTRACT : A core aspect in the field of bibliometrics is the formulation, refinement, and verification of metrics that rate entities in the science domain based on the information contained within the scientific literature corpus. Since these metrics play an increasingly important role in research evaluation, continued scrutiny of current methods is crucial. For example, metrics that are intended to rate the quality of papers should be assessed by correlating them with peer assessments. I approach the problem of assessing metrics with test data based on other objective ratings provided by domain experts which we use as proxies for peer-based quality assessments. This dissertation is an attempt to fill some of the gaps in the literature concerning the evaluation of metrics through test data. Specifically, I investigate two main research questions: (1) what are the best practices when evaluating rankings of academic entities based on test data, and (2), what can we learn about ranking algorithms and impact metrics when they are evaluated using test data? Besides the use of test data to evaluate metrics, the second continual theme of this dissertation is the application and evaluation of indirect ranking algorithms as an alternative to metrics based on direct citations. Through five published journal articles, I present the results of this investigation.