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Number and quality of diagrams in scholarly publications is associated with number of citations

arXiv 2104.14815 ↗First posted 30 Apr 2021cs.DL cs.AIcited by 0

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Abstract (arXiv)

Diagrams are often used in scholarly communication. We analyse a corpus of diagrams found in scholarly computational linguistics conference proceedings (ACL 2017), and find inclusion of a system diagram to be correlated with higher numbers of citations after 3 years. Inclusion of over three diagrams in this 8-page limit conference was found to correlate with a lower citation count. Focusing on neural network system diagrams, we find a correlation between highly cited papers and "good diagramming practice" quantified by level of compliance with a set of diagramming guidelines. Two diagram classification types (one visually based, one mental model based) were not found to correlate with number of citations, but enabled quantification of heterogeneity in those dimensions. Exploring scholarly paper-writing guides, we find diagrams to be a neglected media. This study suggests that diagrams may be a useful source of quality data for predicting citations, and that "graphicacy" is a key skill for scholars with insufficient support at present.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 5 of its 36 references that are in the map. First posted on arXiv 30 Apr 2021.

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References · 5

  1. 2018Predicting citation counts based on deep neural network learning techniquescited by 21
  2. 2016Viziometrics: Analyzing Visual Information in the Scientific Literaturecited by 14
  3. 2020Predicting the Citations of Scholarly Papercited by 7
  4. 2016Quantifying perceived impact of scientific publicationscited by 2
  5. 2020Understanding scholarly Natural Language Processing system diagrams through application of the Richards-Engelhardt frameworkcited by 1

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