4 papers
How to predict creativity ratings from written narratives: A comparison of co-occurrence and textual forma mentis networks
Roberto Passaro, Edith Haim, Massimo Stella
This tutorial paper provides a step-by-step workflow for building and analysing semantic networks from short creative texts. We introduce and compare two widely used text-to-networ…
SpreadPy: A Python tool for modelling spreading activation and superdiffusion in cognitive multiplex networks
Salvatore Citraro, Edith Haim, Alessandra Carini +3
We introduce SpreadPy as a Python library for simulating spreading activation in cognitive single-layer and multiplex networks. Our tool is designed to perform numerical simulation…
Cognitive networks highlight differences and similarities in the STEM mindsets of human and LLM-simulated trainees, experts and academics
Edith Haim, Lars van den Bergh, Cynthia S. Q. Siew +3
Understanding attitudes towards STEM means quantifying the cognitive and emotional ways in which individuals, and potentially large language models too, conceptualise such subjects…
Forma mentis networks predict creativity ratings of short texts via interpretable artificial intelligence in human and GPT-simulated raters
Edith Haim, Natalie Fischer, Salvatore Citraro +2
Creativity is a fundamental skill of human cognition. We use textual forma mentis networks (TFMN) to extract network (semantic/syntactic associations) and emotional features from a…