Defesa in memoriam de Rafael Gomes: Mapeando influenciadores em Ciência: um estudo métrico sobre Fluxos de Informação em Temática do campo da saúde

Abstract

The present research consists of a quantitative methodological proposal, of an exploratory-descriptive nature. It is introduced in the context in which social, economic and scientific development depends, essentially, on the generation of knowledge - product of the information element. It addresses the construction of knowledge as a dynamic phenomenon, whose contents are shared in the form of information flows. In this flow - in science - the quantifiable information is able to reflect the structured knowledge communicated between peers, making the quote emerge as one of the central aspects of formality in scientific communication. The research defines the concept of citation, addressing its different types, characteristics and purposes, as well as the use of citation analysis - especially of authors - for the identification of individuals who influence scientific thinking, here named "influencers in science" (or “scientific influencers”). In view of this, it seeks to answer the questions: how is the information flow structured, based on quotes from authors, in a specific field? In this structure, which authors stand out as scientific influencers? Can the influencers' affiliation and/or collaboration options be related to their interest in contributing to the solution of local problems related to the scientific field? To this end, it proposes to map information flows based on citation links, in global scientific publications in the field of trematodiasis - conceptualizing, characterizing and highlighting the scientific, economic, political and social importance of the field for the United Nations (UN), its agencies and the world. Dissertates on fundamental concepts in Scientometry and on characteristics in metrical studies pertaining to it. The methodological proposal advances, addressing the analysis of citations in the form of a complex network and applying, on it, mathematical resources from Graph Theory. In this scope, it conceptualizes and makes explicit the relevance of the statistical metrics of Degree Centrality, Proximity, Intermediation and Eigenvector, for the identification of the most central influencers in the author's quote network. Operationalization used different current software tools and bibliographic data from worldwide publications on indexed trematodiasis, in the Scopus database, over a 30-year period. 57,544 documents were returned, of which - using the methodology proposed here - a restricted group of scientists from the field was selected, considering the highest volumes of citation links. The application of the four centrality statistics, mentioned above, reduced this portion to just eighteen names in science, hereinafter defined as "high-reach influencers", "medium-range influencers" and "low-reach influencers", according to positions in rankings of graph centralities. It analyzes the citations networks of these eighteen scientific influencers considering the time factor, seeking to extract inferences from the patterns and relationships perceived therein. In a descriptive-exploratory stage, it analyzes qualitative aspects inherent to these names, such as: country of origin, most relevant themes in its publications for the field, academic profile, country and institution of current affiliation, collaboration, volume of total publications and periodicals most used scientific papers. It discusses the analyzes highlighting patterns and characteristics, found in them, that came to answer the initial questions. It concludes, synthetically, that the relevance of the thematic content of each influencer to the field, the age range of the publication and the high penetration capacity of the journals used by the author are factors that seem to affect citation links and centrality positions. Finally, it considers that the methodology developed here is relevant for the identification and mapping of structures and profiles of scientific influencers - from the most diverse areas of knowledge - and useful for the selection of partnerships, improvement of policies in science and technology and, for the development socio-economic, both regional and global.