# Impact of lexical and sentiment factors on the popularity of scientific papers

arXiv: https://arxiv.org/abs/1605.07465 · HTML: https://mlsanity.com/paper/1605.07465/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 24 May 2016.

## Built on by (most cited first, 3 of 3)

- [Did AI get more negative recently?](https://mlsanity.com/paper/2202.13610/) (2022)
- [Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation](https://mlsanity.com/paper/2312.12881/) (2023)
- [Artificial intelligence technologies to support research assessment: A review](https://mlsanity.com/paper/2212.06574/) (2022)

## Abstract (arXiv)

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.