ArticleRoyal Society open science2018
Using text analysis to quantify the similarity and evolution of scientific disciplines.
Article in Royal Society open science, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
11 citing papers in PubMed.
- Validating a novel measure of scientists' disciplinary affiliation that captures its complexity and plasticity.PloS one · 2026Article
- Resilience of science after austerity.PNAS nexus · 2025Article
- Non-White scientists appear on fewer editorial boards, spend more time under review, and receive fewer citations.Proceedings of the National Academy of Sciences of the United States of America · 2023Article
- Statistics in everyone's backyard: An impact study via citation network analysis.Patterns (New York, N.Y.) · 2022Article
- Lexicons of Key Terms in Scholarly Texts and Their Disciplinary Differences: From Quantum Semantics Construction to Relative-Entropy-Based Comparisons.Entropy (Basel, Switzerland) · 2022Article
- Scientometric Analysis of Hiking Tourism and Its Relevance for Wellbeing and Knowledge Management.International journal of environmental research and public health · 2022Article
- Quantifying the rise and fall of scientific fields.PloS one · 2022Article
- Top 50 Most Cited Articles on Thoracic Ossification of Posterior Longitudinal Ligament.Frontiers in surgery · 2022Article
- Categorical and Geographical Separation in Science.Scientific reports · 2018Article
- Using text analysis to quantify the similarity and evolution of scientific disciplines.Royal Society open science · 2018Article
- On entropy research analysis: cross-disciplinary knowledge transfer.Scientometrics · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We use an information-theoretic measure of linguistic similarity to investigate the organization and evolution of scientific fields. An analysis of almost 20 M papers from the past three decades reveals that the linguistic similarity is related but different from experts and citation-based classifications, leading to an improved view on the organization of science. A temporal analysis of the similarity of fields shows that some fields (e.g. computer science) are becoming increasingly central, but that on average the similarity between pairs of disciplines has not changed in the last decades. This suggests that tendencies of convergence (e.g. multi-disciplinarity) and divergence (e.g. specialization) of disciplines are in balance.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.