9 papers
Who Trusts AI with Their Emotions? Trust Formation and Sociodemographic Variation in LLM Use for Emotional Support
Natalia Amat-Lefort, Mert Yazan, Amanda Cercas Curry +1
Trust in AI for emotional support is not universal; it is shaped by who users are, where they come from, and what they value. Yet research in this area lacks validated psychometric…
Affective AI Safety: The Missing Piece in LLM Safety
Carolin Ifländer, Alba Curry, Flor Miriam Plaza-del-Arco +1
AI safety research has focused predominantly on epistemic and physical harms (e.g., misinformation, bias, system reliability) while the risks that arise from AI systems' engagement…
P1SCO: Social Dimensions from a Perspectivist Lens
Amanda Cercas Curry, Gianmarco de Francisci Morales, Luca Maria Aiello
We introduce P1SCO, a dataset of social media comments collected from three distinct platforms, annotated according to ten social dimensions to capture the diversity of social inte…
Learning Perspectivist Social Meaning via Demographic-Conditioned Fusion Embeddings
Amanda Cercas Curry, Lucio La Cava, Luca Maria Aiello +1
Social meaning in language is inherently perspectival, varying across annotator backgrounds, demographics, and ideological positions. However, most NLP systems collapse this variat…
From Chatbots to Confidants: A Cross-Cultural Study of LLM Adoption for Emotional Support
Natalia Amat-Lefort, Mert Yazan, Amanda Cercas Curry +1
Large Language Models (LLMs) are increasingly used not only for instrumental tasks, but as always-available and non-judgmental confidants for emotional support. Yet what drives ado…
Do Large Language Models Adapt to Language Variation across Socioeconomic Status?
Elisa Bassignana, Mike Zhang, Dirk Hovy +1
Humans adjust their linguistic style to the audience they are addressing. However, the extent to which LLMs adapt to different social contexts is largely unknown. As these models i…