4 papers
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…
LLMs can persuade only psychologically susceptible humans on societal issues, via trust in AI and emotional appeals, amid logical fallacies
Alexis Carrillo, Salvatore Citraro, Ali Aghazhadeh Ardebili +5
Scarce longitudinal evidence examines LLMs' persuasiveness and humanness along time-evolving psychological frameworks. We introduce Talk2AI, a longitudinal framework quantifying ps…
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…
Textual forma mentis networks bridge language structure, emotional content and psychopathology levels in adolescents
Alexis Carrillo, Simon Friedrich Roske, Rebeca Ianov-Vitanov +3
We introduce a network-based AI framework for predicting dimensions of psychopathology in adolescents using natural language. We focused on data capturing psychometric scores of so…