Textual Domain

Textual domain analysis focuses on understanding how the characteristics of text—genre, topic, style, and even subtle linguistic fingerprints—influence natural language processing (NLP) tasks. Current research emphasizes developing methods to identify and account for domain differences, often leveraging large language models (LLMs) and exploring techniques like domain adaptation and hierarchical representations to improve model performance across diverse text sources. This work is crucial for enhancing the robustness and generalizability of NLP systems, impacting applications ranging from information retrieval and cybersecurity to social media analysis and legal technology.