Analysis of institutional competitiveness in research using big-variety data

Abstract

Currently, many universities concern with developing into a world-class university and reaching a favorable academic ranking. Since a higher rank could influence important stakeholders such as learners or policy makers. To self-evaluate the ranking performance could be difficult and costly due to the components of the ranking score are not from bibliometrics or research output only, but the survey results which could require enormous effort to collect. Therefore, in this work, we introduce a novel approach to estimate the university ranking based on traditional data, i.e., research output, and the non-traditional data, i.e., number of mentioned counts in social network collected by Altmetrics, and the research performance based on United Nations (UN) Sustainable Development Goals (SDGs). Our approach focuses on estimating the subject areas- ranking in five areas, namely Arts & Humanities, Engineering & Technology, Life Sciences & Medicine, Natural Sciences, and Social Sciences & Management. Once the "score" for each university from the mentioned data has been computed, the outputs are compared to the 2021 QS subject ranking as a benchmark using the Spearman rank-order correlation coefficient as well as the supplementary measurement, the ranking overlapping rate. From the experiment results, our approach, particularly the top-10 ranking in every area performed estimating effectively according to the Spearman coefficient, e.g., Accounting & Finance, Development Studies subjects. For the overlapping rate, it was determined that the experimental results are moderate values for most subjects. Thus, it means that this approach could assist stakeholders in estimating the university's position when comparing universities with similar potential without the surveying.