# What fifty-one years of Linguistics and Artificial Intelligence research tell us about their correlation: A scientometric analysis

arXiv: https://arxiv.org/abs/2411.19858 · HTML: https://mlsanity.com/paper/2411.19858/

## Key facts

- Cited by 8 papers in the map (data through 14 Oct 2026).
- Builds on 24 of its 116 references that are in the map.
- First posted on arXiv 29 Nov 2024.

## Builds on (most cited first, 24 of 24)

- [Attention Is All You Need](https://mlsanity.com/paper/1706.03762/) (2017)
- [BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding](https://mlsanity.com/paper/1810.04805/) (2018)
- [Med-BERT: pre-trained contextualized embeddings on large-scale structured electronic health records for disease prediction](https://mlsanity.com/paper/2005.12833/) (2020)
- [Assessing the Ability of LSTMs to Learn Syntax-Sensitive Dependencies](https://mlsanity.com/paper/1611.01368/) (2016)
- [What BERT is not: Lessons from a new suite of psycholinguistic diagnostics for language models](https://mlsanity.com/paper/1907.13528/) (2019)
- [Model-Agnostic Interpretability of Machine Learning](https://mlsanity.com/paper/1606.05386/) (2016)
- [Colorless green recurrent networks dream hierarchically](https://mlsanity.com/paper/1803.11138/) (2018)
- [Implicit Representations of Meaning in Neural Language Models](https://mlsanity.com/paper/2106.00737/) (2021)
- [Is ChatGPT A Good Translator? Yes With GPT-4 As The Engine](https://mlsanity.com/paper/2301.08745/) (2023)
- [Drug discovery with explainable artificial intelligence](https://mlsanity.com/paper/2007.00523/) (2020)
- [Syntactic Structure from Deep Learning](https://mlsanity.com/paper/2004.10827/) (2020)
- [Machine Culture](https://mlsanity.com/paper/2311.11388/) (2023)
- [On The Evaluation of Machine Translation Systems Trained With Back-Translation](https://mlsanity.com/paper/1908.05204/) (2019)
- [Still a Pain in the Neck: Evaluating Text Representations on Lexical Composition](https://mlsanity.com/paper/1902.10618/) (2019)
- [Assessing Composition in Sentence Vector Representations](https://mlsanity.com/paper/1809.03992/) (2018)
- [Decoding ChatGPT: A Taxonomy of Existing Research, Current Challenges, and Possible Future Directions](https://mlsanity.com/paper/2307.14107/) (2023)
- [Investigating Novel Verb Learning in BERT: Selectional Preference Classes and Alternation-Based Syntactic Generalization](https://mlsanity.com/paper/2011.02417/) (2020)
- [AI-driven Development Is Here: Should You Worry?](https://mlsanity.com/paper/2204.07560/) (2022)
- [Visualizing a Field of Research: A Methodology of Systematic Scientometric Reviews](https://mlsanity.com/paper/1906.04800/) (2019)
- [AutoMLBench: A Comprehensive Experimental Evaluation of Automated Machine Learning Frameworks](https://mlsanity.com/paper/2204.08358/) (2022)
- [Missing author address information in Web of Science-An explorative study](https://mlsanity.com/paper/1807.09944/) (2018)
- [Caveats for the use of Web of Science Core Collection in old literature retrieval and historical bibliometric analysis](https://mlsanity.com/paper/2107.11521/) (2021)
- [The case for the Humanities Citation Index (HuCI): a citation index by the humanities, for the humanities](https://mlsanity.com/paper/2110.00307/) (2021)
- [Web of Science Core Collection's coverage expansion:The forgotten Arts & Humanities Citation Index?](https://mlsanity.com/paper/2312.05524/) (2023)

## Built on by (most cited first, 8 of 8)

- [Machine learning and emoji prediction: How much accuracy can MARBERT achieve?](https://mlsanity.com/paper/2604.21108/) (2026)
- [Does Machine "know" interpersonal pragmatics? Evidence from MARBERT's learning of emoji pragmatics in Arabic digital discourse](https://mlsanity.com/paper/2608.01174/) (2026)
- [Revisiting the syntax of imperatives in Yemeni Arabic: An Agree across phases approach](https://mlsanity.com/paper/2605.08447/) (2026)
- [Current LLMs still cannot 'talk much' about grammar modules: Evidence from syntax](https://mlsanity.com/paper/2603.20114/) (2026)
- [The impact of postediting on AI generative translation in Yemeni context: Translating literary prose by ChatGPT](https://mlsanity.com/paper/2604.16704/) (2026)
- [AI tools in Arab University English classrooms: Looking back and forward](https://mlsanity.com/paper/2607.05403/) (2026)
- [Machine learning and digital pragmatics: Which word category influences emoji use most?](https://mlsanity.com/paper/2608.21975/) (2026)
- [A generative-informed neuro-symbolic framework for syntactic ambiguity resolution: Evidence from Arabic DPs](https://mlsanity.com/paper/2610.02529/) (2026)

## Abstract (arXiv)

There is a strong correlation between linguistics and artificial intelligence (AI), best manifested by deep learning language models. This study provides a thorough scientometric analysis of this correlation, synthesizing the intellectual production over 51 years, from 1974 to 2024. Web of Science Core Collection (WoSCC) database was the data source. The data collected were analyzed by two powerful software, viz., CiteSpace and VOSviewer, through which mapping visualizations of the intellectual landscape, trending issues and (re)emerging hotspots were generated. The results indicate that in the 1980s and 1990s, linguistics and AI (AIL) research was not robust, characterized by unstable publication over time. It has, however, witnessed a remarkable increase of publication since then, reaching 1478 articles in 2023, and 546 articles in January-March timespan in 2024, involving emerging issues including Natural language processing, Cross-sectional study, Using bidirectional encoder representation, and Using ChatGPT and hotspots such as Novice programmer, Prioritization, and Artificial intelligence, addressing new horizons, new topics, and launching new applications and powerful deep learning language models including ChatGPT. It concludes that linguistics and AI correlation is established at several levels, research centers, journals, and countries shaping AIL knowledge production and reshaping its future frontiers.