Learning nuanced cross-disciplinary citation metric normalization using the hierarchical Dirichlet process on big scholarly data

Hafsah Umar, Oggie Arandelovic

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)
2 Downloads (Pure)

Abstract

Citation counts have long been used in academia as a way of measuring, inter alia, the importance of journals, quantifying the significance and the impact of a researcher's body of work, and allocating funding for individuals and departments. For example, the h-index proposed by Hirsch is one of the most popular metrics that utilizes citation analysis to determine an individual's research impact. Among many issues, one of the pitfalls of citation metrics is the unfairness which emerges when comparisons are made between researchers in different fields. The algorithm we described in the present paper learns evidence based, nuanced, and probabilistic representations of academic fields, and uses data collected by crawling Google Scholar to perform field of study based normalization of citation based impact metrics such as the h-index.
Original languageEnglish
Title of host publicationProceedings of the Symposium on Applied Computing
PublisherACM
Pages1842-1847
ISBN (Print)9781450344869
DOIs
Publication statusPublished - 3 Apr 2017
Event32nd ACM SIGAPP Symposium On Applied Computing - Cadi Ayyad University (UCA) of Marrakesh, Marrakech, Morocco
Duration: 3 Apr 20177 Apr 2017
Conference number: 32
http://www.sigapp.org/sac/sac2017/

Conference

Conference32nd ACM SIGAPP Symposium On Applied Computing
Abbreviated titleSAC17
Country/TerritoryMorocco
CityMarrakech
Period3/04/177/04/17
Internet address

Keywords

  • Academic
  • Publication
  • Publishing
  • Quantification
  • University
  • Index
  • Science

Fingerprint

Dive into the research topics of 'Learning nuanced cross-disciplinary citation metric normalization using the hierarchical Dirichlet process on big scholarly data'. Together they form a unique fingerprint.

Cite this