A new parameter for (normalized) evaluation of H-index: countries as a case study

Symmetry in Scientific Collaboration Networks: A Study Using Temporal Graph Data Science and Scientometrics

This article proposes a novel approach that leverages graph theory, machine learning, and graph embedding to evaluate research groups comprehensively. Assessing the performance and impact of research groups is crucial for funding agencies and research institutions, but many traditional methods often fail to capture the complex relationships between the evaluated elements. In this sense, our methodology transforms publication data into graph structures, allowing the visualization and quantification of relationships between researchers, publications, and institutions. By incorporating symmetry properties, we offer a more in-depth evaluation of research groups cohesiveness and structure over time. This temporal evaluation methodology bridges the gap between unstructured scientometrics networks and the evaluation process, making it a valuable tool for decision-making procedures. A case study is defined to demonstrate the potential to provide valuable insights into the dynamics and limitations of research groups, which ultimately reinforces the feasibility of the proposed approach when supporting decision making for funding agencies and research institutions.

Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World

Nowadays, the importance of bibliographic databases (DBs) has increased enormously, as they are the main providers of publication metadata and bibliometric indicators universally used both for research assessment practices and for performing daily tasks. Because the reliability of these tasks firstly depends on the data source, all users of the DBs should be able to choose the most suitable one. Web of Science (WoS) and Scopus are the two main bibliographic DBs. The comprehensive evaluation of the DBs’ coverage is practically impossible without extensive bibliometric analyses or literature reviews, but most DBs users do not have bibliometric competence and/or are not willing to invest additional time for such evaluations. Apart from that, the convenience of the DB’s interface, performance, provided impact indicators and additional tools may also influence the users’ choice. The main goal of this work is to provide all of the potential users with an all-inclusive description of the two main bibliographic DBs by gathering the findings that are presented in the most recent literature and information provided by the owners of the DBs at one place. This overview should aid all stakeholders employing publication and citation data in selecting the most suitable DB.