Linguistic Distancing on Social Media: Indicators of Emotion Regulation Across Age Groups
Quick Answer
This study analyzes linguistic distancing in social media text to understand emotion regulation across age groups, finding that older individuals exhibit greater linguistic distancing, which correlates with improved emotional well-being.
Quick Take
This study analyzes linguistic distancing in social media text to understand emotion regulation across age groups, finding that older individuals exhibit greater linguistic distancing, which correlates with improved emotional well-being. The research provides benchmarks for future studies on emotion regulation in text data.
Key Points
- Linguistic distancing serves as a marker for emotional well-being across age groups.
- Older individuals show proportionally more instances of linguistic distancing.
- The study utilizes large datasets from social media to analyze emotional expression.
- Findings align with psychological research indicating improved well-being with age.
- Research lays groundwork for effective health interventions based on linguistic analysis.
Paper Resources
Article Content
From source RSS / original summaryarXiv: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 large amounts of social media text, a venue where people express their emotions. By investigating how distancing varies across age groups we can better understand how emotion regulation varies with age and provide initial benchmarks on social media data.
We provide additional evidence further strengthening the hypothesis that linguistic distancing occurs in proportionally more instances with age. These findings align with past work in psychology which indicate improved well-being with older age. Better understanding how linguistic distancing changes with age is important because it functions as a marker of well-being and can inform effective health interventions.
We provide a foundation for further exploring emotion regulation through linguistic distancing in text data.
Want this in your inbox every morning?
Daily brief at your local 8am — bilingual EN/中文, free.
More from arXiv cs.CL
See more →Quantifying Prior Dominance in Systems
The study introduces the Normalized Context Utilization (NCU) metric to evaluate Retrieval-Augmented Generation (RAG) systems, revealing that Small Language Models (SLMs) outperform larger models in factual extraction. The findings indicate that traditional scaling laws yield diminishing returns, with a commercial API frequently failing against adversarial evidence due to systemic confidence collapse.