Analysis of Co-authorship Ego networks

Valerio Arnaboldi*, Robin I M Dunbar, Andrea Passarella, Marco Conti

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

12 Citations (Scopus)

Abstract

The availability of co-authorship data from large-scale electronic databases is paving the way for new analyses on human collaboration networks. The complex network of co-authorships can identify specific features that characterise the behaviour of researchers, and impact on their production and performance. In this paper, we analyse a large sample of data regarding scientific publications from Google Scholar. The aim of our analysis is to study a fundamental aspect of coauthorship networks, i.e. the structure of authors’ ego networks. Specifically, we highlight the existence of a hierarchical organisation of these networks in a series of concentric circles, quite similar to that found in general human social networks. In addition, we highlight some properties of the correlation between the ego network structure and the authors scientific productivity, measured in terms of h-index.

Original languageEnglish
Title of host publicationAdvances in Network Science - 12th International Conference and School, NetSci-X 2016, Proceedings
PublisherSpringer Verlag
Pages82-96
Number of pages15
Volume9564
ISBN (Print)9783319283609
DOIs
Publication statusPublished - 2016
MoE publication typeA4 Article in a conference publication
EventInternational Conference and School on Advances in Network Science - Wroclaw, Poland
Duration: 11 Jan 201613 Jan 2016
Conference number: 12

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9564
ISSN (Print)03029743
ISSN (Electronic)16113349

Conference

ConferenceInternational Conference and School on Advances in Network Science
Abbreviated titleNetSci-X
CountryPoland
CityWroclaw
Period11/01/201613/01/2016

Keywords

  • Collaboration networks
  • Ego networks
  • H-index
  • Optimal team size
  • Scientific productivity

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