Impact of lexical and sentiment factors on the popularity of scientific papers
arXiv:1605.07465 · doi:10.1098/rsos.160140
Abstract
We investigate how textual properties of scientific papers relate to the number of citations they receive. Our main finding is that correlations are non-linear and affect differently 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, for typical papers the correlation is in most cases negative. Our analysis of 6 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.
9 pages, 3 figures, 3 tables
References in corpus (6)
- A principal component analysis of 39 scientific impact measures
- Collective emotions online and their influence on community life
- Predicting the long-term citation impact of recent publications
- Self-organization of progress across the century of physics
- Scaling laws and fluctuations in the statistics of word frequencies
- Predictability of extreme events in social media
Cited by in corpus (8)
- Using text analysis to quantify the similarity and evolution of scientific disciplines
- Knowledge Evolution in Physics Research: An Analysis of Bibliographic Coupling Networks
- Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation
- Analyzing Linguistic Complexity and Scientific Impact
- Citations in Software Engineering -- Paper-related, Journal-related, and Author-related Factors
- Did AI get more negative recently?
- PreprintToPaper dataset: connecting bioRxiv preprints with journal publications
- Determining crucial factors for the popularity of scientific articles