Linguistic Signatures

Exploring the Correlation Between Stress and Depression

Abstract

Understanding the linguistic markers associated with depression is crucial for advancing non-invasive mental health assessment techniques. Prior research suggests that language use reflects psychological states, yet identifying specific linguistic patterns associated with depression remains challenging. While sentiment and language use have been studied broadly, few analyses have systematically compared language structure, sentiment, and grammatical features in depressed and non-depressed individuals. This study addresses this gap by examining linguistic markers in a controlled dataset. This study aims to test the hypothesis that certain language patterns, including sentence structure, word choice, and sentiment, can indicate depressive symptoms. Specifically, it seeks to determine if elevated stress levels correlate with identifiable linguistic signatures of depression. Using a dataset of text samples from both depression and control groups, the study employs statistical analysis and linguistic signature methods. Key variables include sentence length, word frequency, and grammatical usage, with sentiment analysis as an additional marker. Results indicate that individuals with depressive symptoms use negatively-toned vocabulary more frequently, exhibit a higher rate of first-person pronouns, and show lower lexical diversity compared to the control group. These patterns suggest tendencies toward self-focus and negative event interpretation. Findings support the development of automated diagnostic tools to detect depression early through language analysis. This approach could improve diagnostic accuracy in mental health and broaden our understanding of the relationship between language and psychological well-being.