Visualizing the world's scientific publications

Rex H.G. Chen, Chi Ming Chen

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Automated methods for the analysis, modeling, and visualization of large-scale scientometric data provide measures that enable the depiction of the state of world scientific development. We aimed to integrate minimum span clustering (MSC) and minimum spanning tree methods to cluster and visualize the global pattern of scientific publications (PSP) by analyzing aggregated Science Citation Index (SCI) data from 1994 to 2011. We hypothesized that PSP clustering is mainly affected by countries' geographic location, ethnicity, and level of economic development, as indicated in previous studies. Our results showed that the 100 countries with the highest rates of publications were decomposed into 12 PSP groups and that countries within a group tended to be geographically proximal, ethnically similar, or comparable in terms of economic status. Hubs and bridging nodes in each knowledge production group were identified. The performance of each group was evaluated across 16 knowledge domains based on their specialization, volume of publications, and relative impact. Awareness of the strengths and weaknesses of each group in various knowledge domains may have useful applications for examining scientific policies, adjusting the allocation of resources, and promoting international collaboration for future developments.

Original languageEnglish
Pages (from-to)2477-2488
Number of pages12
JournalJournal of the Association for Information Science and Technology
Issue number10
Publication statusPublished - 2016 Oct 1


  • automatic classification
  • data mining
  • information mapping

ASJC Scopus subject areas

  • Information Systems
  • Computer Networks and Communications
  • Information Systems and Management
  • Library and Information Sciences


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