6 papers
Natural Language Processing Psychometrics
Edoardo Sebastiano De Duro, Emma Franchino, Massimo Stella
Natural Language Processing (NLP) models predicting mental health outcomes rarely specify what they measure: contextual knowledge, emotional content, or syntactic structure. NLP Ps…
The TEA Nets framework combines AI and cognitive network science to model targets, events and actors in text
Sebastiano Franchini, Alexis Carrillo, Edoardo Sebastiano De Duro +3
We introduce Target-Event-Agent Networks (TEA Nets) as a computational framework to extract subjects (``Agents"), verbs (``Events"), and objects (``Targets") from texts. Grounded i…
Mapping how LLMs debate societal issues when shadowing human personality traits, sociodemographics and social media behavior
Ali Aghazadeh Ardebili, Massimo Stella
Large Language Models (LLMs) can strongly shape social discourse, yet datasets investigating how LLM outputs vary across controlled social and contextual prompting remain sparse. C…
Math Education Digital Shadows for Investigating Learning with GenAI: Mathematics Performance, Anxiety, and Confidence in LLMs
Naomi Esposito, Anthony Tricarico, Luisa Porzio +2
Understanding the impact of large language models (LLMs) on mathematics education requires data on LLMs' mathematical performance and biases. To this end, we introduce Math Educati…
Talk2AI: A Longitudinal Dataset of Human--AI Persuasive Conversations
Alexis Carrillo, Enrique Taietta, Ali Aghazadeh Ardebili +2
Talk2AI is a large-scale longitudinal dataset of 3,080 conversations (totaling 30,800 turns) between human participants and Large Language Models (LLMs), designed to support resear…
Measuring and identifying factors of individuals' trust in Large Language Models
Edoardo Sebastiano De Duro, Giuseppe Alessandro Veltri, Hudson Golino +1
Large Language Models (LLMs) can engage in human-looking conversational exchanges. Although conversations can elicit trust between users and LLMs, scarce empirical research has exa…