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TÜBİTAK has introduced the Incentive Program for International Scientific Publications (UBYT) in 1993 in order to increase the quantity, quality and impact of TR-addressed publications indexed in Web of Science (WoS) and support their authors. Some changes take place from time to time in the algorithms used in the program to identify publications to be supported and to calculate the amounts of monetary support to be paid. The new support algorithm introduced in 2019 aims to improve the shortcomings of the previous one. This paper is a comparative investigation of the impact of the new algorithm on supported journals, publications and the amounts of payments. For this, we first compare the functioning of the old and new support algorithms. We then analyze the impact of the new algorithm on the Program's supported journals lists as well as on the publications having article influence scores (AIS) that were supported in 2015 according to the old algorithm. Findings show that ongoing problems such as providing relatively more support to low impact publications and paying different amounts to publications in different fields do not seem to have completely been solved with the new algorithm. We discuss the major issues with performance-based research funding systems that solely use bibliometric measures to determine the impact of publications and offer some suggestions. [ABSTRACT FROM AUTHOR]

The possibility of creating and easily distributing something via a digital platform creates an enormous material volume. With the increase of scientific publications it becomes harder for scholars to choose the most related and significant resources from the others (Henning & Gunn, 2012). Bibliometrics measures the impact of scholars between each other, but the impact of articles across the entire web is not limited by this. On the other hand, altmetrics measures the impact of articles from the web, alongside bibliometric data. The aim of this study is to investigate the probable relationships between traditional metrics and altmetrics by analysing the PLoS Article-Level Metric (ALM) dataset. [ABSTRACT FROM AUTHOR]