# Who should I Collaborate with? A Comparative Study of Academia and Industry Research Collaboration in NLP

arXiv: https://arxiv.org/abs/2308.04524 · HTML: https://mlsanity.com/paper/2308.04524/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 3 of its 15 references that are in the map.
- First posted on arXiv 21 Jul 2023.

## Builds on (most cited first, 3 of 3)

- [Examining Citations of Natural Language Processing Literature](https://mlsanity.com/paper/2005.00912/) (2020)
- [Measuring academic influence: Not all citations are equal](https://mlsanity.com/paper/1501.06587/) (2015)
- [Generating Extractive Summaries of Scientific Paradigms](https://mlsanity.com/paper/1402.0556/) (2014)

## Abstract (arXiv)

The goal of our research was to investigate the effects of collaboration between academia and industry on Natural Language Processing (NLP). To do this, we created a pipeline to extract affiliations and citations from NLP papers and divided them into three categories: academia, industry, and hybrid (collaborations between academia and industry). Our empirical analysis found that there is a trend towards an increase in industry and academia-industry collaboration publications and that these types of publications tend to have a higher impact compared to those produced solely within academia.