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Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions

Neha Sharma, Kairit Sirts

Abstract

Research exploring linguistic markers in individuals with depression has demonstrated that language usage can serve as an indicator of mental health. This study investigates the impact of discussion topic as context on linguistic markers and emotional expression in depression, using a Reddit dataset to explore interaction effects. Contrary to common findings, our sentiment analysis revealed a broader range of emotional intensity in depressed individuals, with both higher negative and positive sentiments than controls. This pattern was driven by posts containing no emotion words, revealing the limitations of the lexicon based approaches in capturing the full emotional context. We observed several interesting results demonstrating the importance of contextual analyses. For instance, the use of 1st person singular pronouns and words related to anger and sadness correlated with increased positive sentiments, whereas a higher rate of present-focused words was associated with more negative sentiments. Our findings highlight the importance of discussion contexts while interpreting the language used in depression, revealing that the emotional intensity and meaning of linguistic markers can vary based on the topic of discussion.

Context is Important in Depressive Language: A Study of the Interaction Between the Sentiments and Linguistic Markers in Reddit Discussions

Abstract

Research exploring linguistic markers in individuals with depression has demonstrated that language usage can serve as an indicator of mental health. This study investigates the impact of discussion topic as context on linguistic markers and emotional expression in depression, using a Reddit dataset to explore interaction effects. Contrary to common findings, our sentiment analysis revealed a broader range of emotional intensity in depressed individuals, with both higher negative and positive sentiments than controls. This pattern was driven by posts containing no emotion words, revealing the limitations of the lexicon based approaches in capturing the full emotional context. We observed several interesting results demonstrating the importance of contextual analyses. For instance, the use of 1st person singular pronouns and words related to anger and sadness correlated with increased positive sentiments, whereas a higher rate of present-focused words was associated with more negative sentiments. Our findings highlight the importance of discussion contexts while interpreting the language used in depression, revealing that the emotional intensity and meaning of linguistic markers can vary based on the topic of discussion.
Paper Structure (29 sections, 8 figures, 9 tables)

This paper contains 29 sections, 8 figures, 9 tables.

Figures (8)

  • Figure 1: Sentiment distribution of both groups.
  • Figure 2: The linear regression model coefficients of the statistically significant features and their impact on the sentiment difference.
  • Figure 3: Sentiment distribution across data splits.
  • Figure 4: Median anger and sadness scores across data splits.
  • Figure 5: Confusion matrices of the VADER and RoBERTa predicted values compared to the manually annotated subset of 200 posts.
  • ...and 3 more figures