Can models of author intention support quality assessment of content?

A.J. Casey, B. Webber, Dorota Lowacka

Research output: Contribution to journalConference articleScientificpeer-review

Abstract

Academics seek to find, understand and critically review the work of other researchers through published scientific articles. In recent years, the volume of available information has significantly increased, partly due to technological advancements and partly due to pressures on academics to 'publish or perish'. This amount of papers presents a challenge not only for the peer-review process but also for readers, particularly inexperienced readers, to find publications of high quality. Whilst one might rely on citation or journal rankings to help guide this decision, this approach may not be completely reliable due to biased peer-review processes and the fact that the citation count of an article does not per se indicate its quality. Here, we analyse how expected author intentions in a Related Work section can be used to indicate its quality. We show that author intentions can predict the quality with reasonable accuracy and propose that similar approaches could be used in other sections to provide an overall picture of quality. This approach could be useful in supporting peer-review processes and for a reader in prioritising articles to read. © 2019 CEUR-WS. All rights reserved.
Original languageEnglish
JournalCEUR Workshop Proceedings
Volume2414
Pages (from-to)92-99
Number of pages8
ISSN1613-0073
Publication statusPublished - 2019
Externally publishedYes
MoE publication typeA4 Article in conference proceedings

Fields of Science

  • Article Quality
  • Author Intentions
  • Supporting peer-review
  • Information retrieval
  • Natural language processing systems
  • Article qualities
  • Peer review
  • Peer-review process
  • Publish or perish
  • Reasonable accuracy
  • Scientific articles
  • Technological advancement
  • Digital libraries
  • 113 Computer and information sciences

Cite this

Casey, A. J., Webber, B., & Lowacka, D. (2019). Can models of author intention support quality assessment of content? CEUR Workshop Proceedings, 2414, 92-99.