ArticleRoyal Society open science2016
Impact of lexical and sentiment factors on the popularity of scientific papers.
Article in Royal Society open science, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 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
9 citing papers in PubMed.
- Authorship, titles and open access as drivers of citation performance in orthopaedics: a scientometric analysis.Journal of orthopaedics and traumatology : official journal of the Italian Society of Orthopaedics and Traumatology · 2026Article
- PreprintToPaper dataset: connecting bioRxiv preprints with journal publications.Scientific data · 2026Article
- Did AI get more negative recently?Royal Society open science · 2023Article
- Linguistic positivity in soft and hard disciplines: temporal dynamics, disciplinary variation, and the relationship with research impact.Scientometrics · 2023Article
- Revealing semantic and emotional structure of suicide notes with cognitive network science.Scientific reports · 2021Article
- Title does matter: a cross-sectional study of 30 journals in the Medical Laboratory Technology category.Biochemia medica · 2020Article
- 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
- Knowledge evolution in physics research: An analysis of bibliographic coupling networks.PloS one · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We investigate how textual properties of scientific papers relate to the number of citations they receive. Our main finding is that correlations are nonlinear and affect differently the most cited and typical papers. For instance, we find that, in most journals, short titles correlate positively with citations only for the most cited papers, whereas for typical papers, the correlation is usually negative. Our analysis of six different factors, calculated both at the title and abstract level of 4.3 million papers in over 1500 journals, reveals the number of authors, and the length and complexity of the abstract, as having the strongest (positive) influence on the number of citations.
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.