Viewing computer science through citation analysis: Salton and Bergmark Redux

Abstract

Computer science has experienced dramatic growth and diversification over the last twenty years. Towards a current understanding of the structure of this discipline, we analyze a large sample of the computer science literature from the DBLP database. For insight on the features of this cohort and the relationship within its components, we have constructed article level clusters based on either direct citations or co-citations, and reconciled them with major and minor subject categories in the All Science Journal Classification. We describe complementary insights from clustering by direct citation and co-citation, and both point to the increase in computer science publications and their scope. Our analysis reveals crosscategory clusters, some that interact with external fields, such as the biological sciences, while others remain inward looking. Overall, we document an increase in computer science publications and their scope.

Finding scientific communities in citation graphs: Articles and authors

“…For reproducibility, we used a seed value of 2020. For analysis with Graclus, we used a previous installation of the source code as described in Devarakonda et al (2020). Our initial experiment (Figure 1) was to cluster the 2.16 million publications in the imm_1 data set, which resulted in 134,094 clusters using MCL and 142,005 clusters using Leiden.…”

“…To evaluate clusters and shuffled-citation clusters generated by MCL, Leiden, or Graclus, we examined edge (citation) densities by intracluster conductance (Devarakonda et al, 2020;Emmons et al, 2016). The conductance of a cluster S, denoted (S ), is defined using the formula:…”

“…Leiden has similar properties and has been used with citation data. Graclus is a spectral clustering method that we have used to construct article clusters from citation data (Devarakonda, Korobskiy, Warnow, & Chacko, 2020) and has been evaluated by others (Almeida, Guedes, Meira, & Zaki, 2011;Šubelj, van Eck, & Waltman, 2016). Graclus requires that the number of clusters to be formed is specified at runtime.…”

Center-Periphery Structure in Communities: Extracellular Vesicles

“…For this, we use the Graclus clustering method (Dhillon et al, 2007). Graclus has been previously used to cluster bibliometric data (Dhillon et al, 2007;Devarakonda et al, 2020;Šubelj et al, 2016), but here we use it to split a given cluster into two sub-clusters. We use Graclus to optimize its default criterion, which is the normalized cut criterion.…”

fluxo temporal de termos relevantes

“…Em 1974 foram publicados 419 artigos relacionados à computação, cujas 3.812 referências em todos eles foram analisadas por Salton & Bergmark (1979), num dos primeiros estudos bibliométricos dessa ciência, para a qual concluíram existir naquele momento três principais áreas: fundamentos teóricos, hardware e software. Partindo da mesma base metodológica, 45 anos depois, Devarakonda et al (2020) concluíram que a ciência da computação não somente expandiu em volume, mas também em subáreas interdisciplinares conforme cerca de 8 milhões de documentos analisados. Bush (1945, pág.95) já predissera o crescimento da informação e suas consequências ao pontuar sobre a necessidade da interdisciplinaridade:…”