# Analyzing the Impact of Companies on AI Research Based on Publications

arXiv: https://arxiv.org/abs/2310.20444 · HTML: https://mlsanity.com/paper/2310.20444/

## Key facts

- Cited by 5 papers in the map (data through 14 Oct 2026).
- Builds on 17 of its 56 references that are in the map.
- First posted on arXiv 31 Oct 2023.

## Builds on (most cited first, 17 of 17)

- [The Hardware Lottery](https://mlsanity.com/paper/2009.06489/) (2020)
- [Artificial Intelligence: the global landscape of ethics guidelines](https://mlsanity.com/paper/1906.11668/) (2019)
- [The role of artificial intelligence in achieving the Sustainable Development Goals](https://mlsanity.com/paper/1905.00501/) (2019)
- [The History Began from AlexNet: A Comprehensive Survey on Deep Learning Approaches](https://mlsanity.com/paper/1803.01164/) (2018)
- [The De-democratization of AI: Deep Learning and the Compute Divide in Artificial Intelligence Research](https://mlsanity.com/paper/2010.15581/) (2020)
- [The Grey Hoodie Project: Big Tobacco, Big Tech, and the threat on academic integrity](https://mlsanity.com/paper/2009.13676/) (2020)
- [The AI Index 2021 Annual Report](https://mlsanity.com/paper/2103.06312/) (2021)
- [Gathering Strength, Gathering Storms: The One Hundred Year Study on Artificial Intelligence (AI100) 2021 Study Panel Report](https://mlsanity.com/paper/2210.15767/) (2022)
- [A narrowing of AI research?](https://mlsanity.com/paper/2009.10385/) (2020)
- [Large-scale comparison of bibliographic data sources: Scopus, Web of Science, Dimensions, Crossref, and Microsoft Academic](https://mlsanity.com/paper/2005.10732/) (2020)
- [The Privatization of AI Research(-ers): Causes and Potential Consequences -- From university-industry interaction to public research brain-drain?](https://mlsanity.com/paper/2102.01648/) (2021)
- [A 20-Year Community Roadmap for Artificial Intelligence Research in the US](https://mlsanity.com/paper/1908.02624/) (2019)
- [No computation without representation: Avoiding data and algorithm biases through diversity](https://mlsanity.com/paper/2002.11836/) (2020)
- [Do altmetrics point to the broader impact of research? An overview of benefits and disadvantages of altmetrics](https://mlsanity.com/paper/1406.7091/) (2014)
- [Ethical Considerations and Statistical Analysis of Industry Involvement in Machine Learning Research](https://mlsanity.com/paper/2006.04541/) (2020)
- [New data, new possibilities: Exploring the insides of Altmetric.com](https://mlsanity.com/paper/1408.0135/) (2014)
- [Citation Analysis with Microsoft Academic](https://mlsanity.com/paper/1609.05354/) (2016)

## Built on by (most cited first, 5 of 5)

- [Real-World Gaps in AI Governance Research](https://mlsanity.com/paper/2505.00174/) (2025)
- [Big Tech influence over AI research revisited: memetic analysis of attribution of ideas to affiliation](https://mlsanity.com/paper/2312.12881/) (2023)
- [Quantifying the Knowledge Proximity Between Academic and Industry Research: An Entity and Semantic Perspective](https://mlsanity.com/paper/2602.05211/) (2026)
- [Big Tech-Funded AI Papers Have Higher Citation Impact, Greater Insularity, and Larger Recency Bias](https://mlsanity.com/paper/2512.05714/) (2025)
- [From Bias to Balance: Fairness-Aware Paper Recommendation for Equitable Peer Review](https://mlsanity.com/paper/2602.22438/) (2026)

## Abstract (arXiv)

Artificial Intelligence (AI) is one of the most momentous technologies of our time. Thus, it is of major importance to know which stakeholders influence AI research. Besides researchers at universities and colleges, researchers in companies have hardly been considered in this context. In this article, we consider how the influence of companies on AI research can be made measurable on the basis of scientific publishing activities. We compare academic- and company-authored AI publications published in the last decade and use scientometric data from multiple scholarly databases to look for differences across these groups and to disclose the top contributing organizations. While the vast majority of publications is still produced by academia, we find that the citation count an individual publication receives is significantly higher when it is (co-)authored by a company. Furthermore, using a variety of altmetric indicators, we notice that publications with company participation receive considerably more attention online. Finally, we place our analysis results in a broader context and present targeted recommendations to safeguard a harmonious balance between academia and industry in the realm of AI research.