A new approach for modeling researcher community based on scientific article metadata using natural language processing

Daniel Siahaan, Achmad Maududie, Slamin, Agus Subekti, Prihandoko, Hotniar Siringoringo

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

3 Citations (Scopus)

Abstract

The Ministry of Research, Technology, and Higher Education of Indonesia has requirements to answer five main questions, i.e. what are the most popular research topics; which research topics tend to diminish; what are the trending research topics; who are the most influential researchers in a specific research topic, and; who are leading researchers in a specific topic. This study is a part of our ongoing main project to develop a scientific community model based on scientific article publication. This paper introduces a new approach to model a virtual researcher network using metadata of articles. We modified PageRank to develop a term graph and author-Term graph for this purpose. Based on the preliminary results, the model could answer the five aforementioned questions.

Original languageEnglish
Title of host publication7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages386-390
Number of pages5
ISBN (Electronic)9781509054015
DOIs
Publication statusPublished - 11 May 2017
Event7th International Conference on Information Science and Technology, ICIST 2017 - Da Nang, Viet Nam
Duration: 16 Apr 201719 Apr 2017

Publication series

Name7th International Conference on Information Science and Technology, ICIST 2017 - Proceedings

Conference

Conference7th International Conference on Information Science and Technology, ICIST 2017
Country/TerritoryViet Nam
CityDa Nang
Period16/04/1719/04/17

Keywords

  • article metadata
  • author-Term graph
  • natural language processing
  • researcher community
  • term graph

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