As an efficient approach to understand, generate, and process natural
language texts, research in natural language processing (NLP) has exhibited a
rapid spread and wide adoption in recent years. Given the increasing amount of
research work in this area, several NLP-related approaches have been surveyed
in the research community. However, a comprehensive study that categorizes
established topics, identifies trends, and outlines areas for future research
remains absent to this day. Contributing to closing this gap, we have
systematically classified and analyzed research papers included in the ACL
Anthology. As a result, we present a structured overview of the research
landscape, provide a taxonomy of fields-of-study in NLP, analyze recent
developments in NLP, summarize our findings, and highlight directions for
future work.Comment: Accepted to the 14th International Conference on Recent Advances in
Natural Language Processing (RANLP 2023