Highly Cited Publications index (HCP) for individual evaluation : applications in Brazilian information metric studies

• Autor(a) principal: Maricato, João de Melo
• Data de Publicação: 2021
• Outros Autores: Santos, Priscila Rodrigues dos
• Tipo de documento: Artigo
• Idioma: por
• Título da fonte: Repositório Institucional da UnB
• Texto Completo: https://repositorio.unb.br/handle/10482/45193; https://orcid.org/0000-0001-9162-6866; https://orcid.org/0000-0002-1897-8838
• topic: Bibliometria; Estudos Métricos da Informação (EMI); Highly cited publications (HCP)

The use of different bibliometric indicators to analyze the individual scientific production of researchers constantly raises questions among several authors. Based on this problem, Waltman, Van Eck and Wouters (2013) propose a methodology that values highly cited papers (high impact) over low cited papers (low impact). To this end, the authors developed a stylized Highly Cited Publications (HCP) index aiming to minimize some limitations inherent to the metrics used to evaluate scientists. The present work proposes to carry out the empirical application of the HCP index stylized by the authors to researchers in the field of Information Metrics Studies (IMS) in Brazil in order to identify its potentialities and limitations. The research data was limited to 101 researchers in the area of IMS in Brazil, who had their production and citation data extracted from Google Citations in the month of July 2020, being evaluated different data sets in two distinct time periods (1941-2020 versus 2010-2020), for the purpose of comparative analysis, being possible to observe that according to Person's correlation, the use of different data sets, as long as they respect the same variables, do not show significant changes in the ranking of the researchers' HCP indexes. The use of the stylized HCP index is interesting for the identification of highly cited publications and can be used to complement the evaluation indicators, but it presents limitations that may inhibit its use, for example, the negative indexes of specific researchers.