Bilateral Co-authorship Indicators Based on Fractional Counting

Fractional counting of authorship to quantify scientific research output

We investigate the problem of counting co-authorhip in order to quantify the impact and relevance of scientific research output through normalized h-index and g-index. We use the papers whose authors belong to a subset of full professors of the Italian Settore Scientifico Disciplinare (SSD) FIS01 Experimental Physics. In this SSD two populations, characterized by the number of co-authors of eac...

Co-authorship network analysis and social network indicators of coronavirus research

Background and aim: The aim of this study was to examine the status of documents related to coronavirus based on scientometric indicators and to draw a co-authorship map of authors, organizations and countries producing an article to get to know this field as much as possible. Materials and methods: This applied-scientometric was conducted using social network analysis. The statistical populati...

On Spectral Partitioning of Co-authorship Networks

Abstract. Spectral partitioning is a well known method in the area of graph and matrix analysis. Several approaches based on spectral partitioning and spectral clustering were used to detect structures in real world networks and databases. In this paper, we explore two community detection approaches based on the spectral partitioning to analyze a coauthorship network. The partitioning exploits ...

Refining our policies on co-authorship requirements

On co-authorship for author disambiguation

Author name disambiguation deals with clustering the same-name authors into different individuals. To attack the problem, many studies have employed a variety of disambiguation features such as coauthors, titles of papers/publications, topics of articles, emails/affiliations, etc. Among these, co-authorship is the most easily accessible and influential, since inter-person acquaintances represen...