  Large language models (LLMs) are a class of language models that have
demonstrated outstanding performance across a range of natural language
processing (NLP) tasks and have become a highly sought-after research area,
because of their ability to generate human-like language and their potential to
revolutionize science and technology. In this study, we conduct bibliometric
and discourse analyses of scholarly literature on LLMs. Synthesizing over 5,000
publications, this paper serves as a roadmap for researchers, practitioners,
and policymakers to navigate the current landscape of LLMs research. We present
the research trends from 2017 to early 2023, identifying patterns in research
paradigms and collaborations. We start with analyzing the core algorithm
developments and NLP tasks that are fundamental in LLMs research. We then
investigate the applications of LLMs in various fields and domains including
medicine, engineering, social science, and humanities. Our review also reveals
the dynamic, fast-paced evolution of LLMs research. Overall, this paper offers
valuable insights into the current state, impact, and potential of LLMs
research and its applications.
