We propose a “layered structured network diagram,” which consists of layers of time differences. We have implemented a tool called “NeL” for handling layered structured network diagrams. Layered structured network diagrams have multiple accumulated layers and are not single diagrams. Using this layered structure, time differences can be included in one diagram. In addition, various type of info...

Research collaboration is studied in different research areas, so as to provide useful insights on how researchers combine existing distributed scientific knowledge and transform it into new knowledge. Commonly used metrics for measuring research collaborative activity include, among others, the co-authored publications (concerned with who works with whom) and the citations (concerned with who ...

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Bioinformatics is an interdisciplinary research field that applies advanced computational techniques to biological data. Bibliometrics analysis has recently been adopted to understand the knowledge structure of a research field by citation pattern. In this paper, we explore the knowledge structure of Bioinformatics from the perspective of a core open access Bioinformatics journal, BMC Bioinform...

this research examines the association between co-authorship network centrality (degree, closeness, betweenness, eigenvector, bonacich flow betweenness) and productivity of information science researchers. the research population includes all those researchers who have published at least one record in one of the twenty journals of information science which has an impact factor of 0.635 as a min...

By publishing papers together, academic authors can form a co-authorship network, modeling the collaboration among them. This paper presents a data-driven study by crawling and analyzing the vast majority of author profiles of Google Scholar. We make the following major contributions: (1) We present a demographic analysis and get an informative overview of the authors from different aspects, su...

In this paper, we explore a set of novel features for authorship attribution of documents. These features are derived from a word network representation of natural language text. As has been noted in previous studies, natural language tends to show complex network structure at word level, with low degrees of separation and scale-free (power law) degree distribution. There has also been work on ...