Using full-text data to create improved term maps

Nees Jan Van Eck, Ludo Waltman, Min Song, Yoo Kyung Jeong

Research output: Contribution to conferencePaper

Abstract

A term map offers a visualization of a network of terms that co-occur in scientific publications. Term maps are usually created based on the titles and abstracts of publications. In this paper, we explore the use of full-text data for creating term maps. We create and compare a series of term maps based on the full text of publications in Journal of Informetrics. We use our results to discuss the advantages and disadvantages of different approaches for creating term maps.

Original languageEnglish
Pages1136-1141
Number of pages6
Publication statusPublished - 2017
Event16th International Conference on Scientometrics and Informetrics, ISSI 2017 - Wuhan, China
Duration: 2017 Oct 162017 Oct 20

Other

Other16th International Conference on Scientometrics and Informetrics, ISSI 2017
CountryChina
CityWuhan
Period17/10/1617/10/20

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Applied Mathematics
  • Modelling and Simulation
  • Statistics and Probability
  • Management Science and Operations Research

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  • Cite this

    Van Eck, N. J., Waltman, L., Song, M., & Jeong, Y. K. (2017). Using full-text data to create improved term maps. 1136-1141. Paper presented at 16th International Conference on Scientometrics and Informetrics, ISSI 2017, Wuhan, China.