| Download | - View final version: A diachronic analysis of paradigm shifts in NLP research: when, how, and why? (PDF, 627 KiB)
|
|---|
| DOI | Resolve DOI: https://doi.org/10.18653/v1/2023.emnlp-main.142 |
|---|
| Author | Search for: Pramanick, Aniket; Search for: Hou, Yufang; Search for: Mohammad, Saif1; Search for: Gurevych, Iryna |
|---|
| Affiliation | - National Research Council Canada. Digital Technologies
|
|---|
| Format | Text, Article |
|---|
| Conference | 2023 Conference on Empirical Methods in Natural Language Processing, December 6-10, 2023, Singapore |
|---|
| Abstract | Understanding the fundamental concepts and trends in a scientific field is crucial for keeping abreast of its continuous advancement. In this study, we propose a systematic framework for analyzing the evolution of research topics in a scientific field using causal discovery and inference techniques. We define three variables to encompass diverse facets of the evolution of research topics within NLP and utilize a causal discovery algorithm to unveil the causal connections among these variables using observational data. Subsequently, we leverage this structure to measure the intensity of these relationships. By conducting extensive experiments on the ACL Anthology corpus, we demonstrate that our framework effectively uncovers evolutionary trends and the underlying causes for a wide range of NLP research topics. Specifically, we show that tasks and methods are primary drivers of research in NLP, with datasets following, while metrics have minimal impact. |
|---|
| Publication date | 2023-12-06 |
|---|
| Publisher | Association for Computational Linguistics |
|---|
| Licence | |
|---|
| In | |
|---|
| Language | English |
|---|
| Peer reviewed | Yes |
|---|
| Export citation | Export as RIS |
|---|
| Report a correction | Report a correction (opens in a new tab) |
|---|
| Record identifier | 5212f03e-f75c-4130-8675-7c303ca22598 |
|---|
| Record created | 2024-01-08 |
|---|
| Record modified | 2024-01-08 |
|---|
