Can models of author intention support quality assessment of content?

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

Research output: Contribution to journalConference articleScientificpeer-review


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
Pages (from-to)92-99
Number of pages8
Publication statusPublished - 2019
MoE publication typeA4 Article in conference proceedings
EventJoint Workshop on Bibliometric-enhanced Information Retrieval and Natural Language Processing for Digital Libraries co with the 42nd International ACM SIGIR Conference on Research and Development in Information Retrieval (SIGIR 2019) - Paris, France
Duration: 25 Jul 201925 Jul 2019
Conference number: 4

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

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