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Measuring discursive influence across scholarship.

Aaron Gerow1, Yuening Hu2, Jordan Boyd-Graber3,4,5,6

  • 1Department of Computing, Goldsmiths, University of London, New Cross, London SE14 6NW, United Kingdom; a.gerow@gold.ac.uk jevans@uchicago.edu.

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Summary
This summary is machine-generated.

Scholarly influence is complex and not fully captured by citations alone. New methods incorporating author and venue context better assess diverse, long-term academic impact.

Keywords:
probabilistic modelingscholarly influencescience of science

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Area of Science:

  • Bibliometrics and Scientometrics
  • Computational Social Science
  • Network Science

Background:

  • Citations are a primary but limited measure of scholarly influence.
  • Citation counts follow preferential attachment and a 'news cycle,' potentially missing sustained or indirect impact.
  • Existing methods do not fully account for contextual factors like authorship and publication venue.

Purpose of the Study:

  • To develop a novel measure of scholarly influence that incorporates contextual features beyond citation counts.
  • To analyze how authorship, affiliation, and publication venue interact with content to shape future scholarship.
  • To provide a more comprehensive assessment of academic impact, addressing limitations of traditional citation metrics.

Main Methods:

  • Adapted dynamic topic models to track discourse shifts and incorporate metadata (authorship, affiliation, venue).
  • Analyzed large-scale datasets of physics research abstracts (500,000; 102 years) and general scholarship (JSTOR, 2 million articles; 130 years).
  • Developed a document influence measure that predicts citations and quantifies contextual impact.

Main Results:

  • The new influence measure predicts citations and identifies factors boosting impact (e.g., Nobel Prizes, high-rank affiliations).
  • Citation analysis alone undervalues authors with long-term persistence and work influential across multiple topics or ahead of its time.
  • Discursive influence metrics reveal a broader spectrum of impact than citation counts.

Conclusions:

  • The proposed measure offers a more nuanced understanding of scholarly influence by integrating content and context.
  • This approach helps correct citation biases and acknowledges diverse contributions that gain appreciation over longer periods.
  • Enhanced metrics can improve the recognition of varied forms of academic impact and their historical trajectories.