Linguistic Marker

Linguistic markers are patterns in language reflecting various aspects of the speaker or writer, such as emotional state, demographic traits, or even the presence of cognitive impairments. Current research focuses on improving the accuracy and robustness of identifying these markers using natural language processing (NLP) techniques, including supervised learning classifiers and pre-trained language models, while also addressing challenges like contextual variations and the impact of tools like large language models on their reliability. This work has significant implications for diverse fields, including mental health diagnostics, bias detection in healthcare records, and authorship attribution, offering potential for improved automated analysis of textual data.