arXiv:2606.30957v1 Announce Type: new Abstract: Managing our emotional responses to events is key to emotional well-being, a process referred to as emotion regulation in psychology. Previous work has established that the degree to which we distance events is a type of emotion regulation. When we psychologically distance from events there can be markers in our language. These markers have been referred to as linguistic distancing. We build upon a previous metric to operationalize linguistic distancing, and explore how it changes across the lifespan. We explore this systematically by analyzing l
This paper leverages advanced computational linguistics, likely enabled by recent AI breakthroughs, to analyze complex psychological phenomena in a quantitative manner.
Understanding linguistic markers of emotion regulation across age groups could lead to more sophisticated AI models for mental health, social interaction analysis, and personalized communication.
The ability to systematically identify and measure linguistic distancing provides a new tool for psychological research and could inform the development of more empathetic or psychologically aware AI systems.
- · AI researchers
- · Psychology researchers
- · Mental health AI applications
- · Social media platforms (for content moderation/insight)
- · Traditional qualitative psychology methods
- · Generative AI without emotional intelligence models
AI models could be trained to detect and interpret emotional regulation strategies in real-time social media interactions.
This could lead to personalized digital interventions or content recommendations designed to support emotional well-being based on linguistic cues.
These capabilities might be integrated into AI agents, allowing them to adapt their communication style to better manage human emotions and relationships in virtual environments.
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