Uma análise cienciométrica das subáreas da ciência da computação

• Autor(a) principal: Braga, Adriano Honorato
• Data de Publicação: 2013
• Tipo de documento: Dissertação
• Idioma: por
• Título da fonte: Repositório Institucional da UFG
• Texto Completo: http://repositorio.bc.ufg.br/tede/handle/tede/3772
• topic: Análise bibliométrica; Métricas; PageRank; Fator de impacto; ACM; Subáreas; Ciências da computação; Bibliometric analysis; Metrics; Impact factor; Subfields; Computer science; PageRank; ACM; CIENCIAS EXATAS E DA TERRA::CIENCIA DA COMPUTACAO

Scientific studies about bibliographic productions in specific areas of science are becoming common, mainly in the last decade. Such investigations usually make use of bibliometric indices to evaluate relevance of the actors that take part in scientific production process, such as: authors, institutions, venues, and subfields of the scientific area being considered. Many studies have investigated the scientific production in computer science under different views. In this work, its presented an analysis about the production of scientific article in computer science and an analysis of citations among subfields, derived from article citation network. The work present novelty not only because it considers many common sense fields in computer science, but also because it presents citation related measures chronologically. The following bibliometric measures were used: number of publications in each subfield, number of citations received by a subfield, Impact Factor, PageRank, and a measure of diversity of subfields that cite a given subfield. Most of those metrics were proposed to study articles, web pages or scientific journals and they had to be adapted to be applied to the subfield analysis. This work has derived many interesting information to computer science community. It presents an historical evolution of the computer science subfields, showing how interest in publishing in subfields and how citations among subfields have evolved during the years. Some trends are revealed, some patterns are recognized to be stable along the time and some subfields are becoming less attractive than others.