Analyzing a Decade of Evolution: Trends in Natural Language Processing

Richard A. A. Jonker, Tiago Melo Almeida, Sérgio Matos

Abstract: Natural Language Processing (NLP) stands at the forefront of the rapidly evolving landscape of Machine Learning, witnessing the emergence and evolution of diverse methodologies over the past decade. This study delves into the dynamic trends within the NLP domain, specifically spanning the years 2010 to 2022, through an empirical analysis of papers presented at conferences hosted by the Association for Computational Linguistics (ACL). We utilize ChatGPT in order to extract meaningful information from the data before performing an in depth analysis. Our investigation encompasses an exploration of several key aspects, namely computational trends, research trends and geographic trends. We further investigate the entry cost into NLP, the longevity of hardware and the environmental impact of NLP. The code to run our system is publicly available at https://github.com/ieeta-pt/nlp-trends.