Detecting the severity of human depression in multi-party text conversations

Key Points

• The central aim is to assess how depression severity can be evaluated through analysis of text in multi-party conversations.
• Utilized natural language processing techniques for emotional analysis
• Analyzed text data from multiple conversational participants
• Performed statistical evaluations to determine depression severity
• Identified distinct indicators of depression severity through text patterns
• Achieved high accuracy in emotion classification
• Demonstrated effectiveness of multi-party text analysis in assessing emotional states