# Analyzing Linguistic Complexity and Scientific Impact

arXiv: https://arxiv.org/abs/1907.11843 · HTML: https://mlsanity.com/paper/1907.11843/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 27 Jul 2019.

## Built on by (most cited first, 6 of 6)

- [On predicting research grants productivity](https://mlsanity.com/paper/2106.10700/) (2021)
- [Artificial intelligence technologies to support research assessment: A review](https://mlsanity.com/paper/2212.06574/) (2022)
- [The Effect of Gender Diversity on Scientific Team Impact: A Team Roles Perspective](https://mlsanity.com/paper/2512.23429/) (2025)
- [Measuring Research Difficulty of Academic Papers: A Case Study in Natural Language Processing](https://mlsanity.com/paper/2606.25307/) (2026)
- [Measuring the Novelty of Biomedical Papers Using the Latent Distances between Knowledge Units](https://mlsanity.com/paper/2609.05175/) (2026)
- [Do Reviewers Still Reward Lexical Complexity? A Frozen-Rater Study of Preference Drift in 124K ICLR Reviews](https://mlsanity.com/paper/2609.08475/) (2026)

## Abstract (arXiv)

The number of publications and the number of citations received have become the most common indicators of scholarly success. In this context, scientific writing increasingly plays an important role in scholars' scientific careers. To understand the relationship between scientific writing and scientific impact, this paper selected 12 variables of linguistic complexity as a proxy for depicting scientific writing. We then analyzed these features from 36,400 full-text Biology articles and 1,797 full-text Psychology articles. These features were compared to the scientific impact of articles, grouped into high, medium, and low categories. The results suggested no practical significant relationship between linguistic complexity and citation strata in either discipline. This suggests that textual complexity plays little role in scientific impact in our data sets.