most citedY Social: an LLM-powered Social Media Digital Twin

3 citations · 4 across the 6 of their papers we have counts for

collaborators

6 papers

cs.AI20243 cited

Y Social: an LLM-powered Social Media Digital Twin

Giulio Rossetti, Massimo Stella, Rémy Cazabet +7

In this paper we introduce Y, a new-generation digital twin designed to replicate an online social media platform. Digital twins are virtual replicas of physical systems that allow…

cs.SI2024

From Perils to Possibilities: Understanding how Human (and AI) Biases affect Online Fora

Virginia Morini, Valentina Pansanella, Katherine Abramski +4

Social media platforms are online fora where users engage in discussions, share content, and build connections. This review explores the dynamics of social interactions, user-gener…

cs.LG2024

Redefining Event Types and Group Evolution in Temporal Data

Andrea Failla, Rémy Cazabet, Giulio Rossetti +1

Groups -- such as clusters of points or communities of nodes -- are fundamental when addressing various data mining tasks. In temporal data, the predominant approach for characteri…

cs.CY2023

Cognitive network science reveals bias in GPT-3, ChatGPT, and GPT-4 mirroring math anxiety in high-school students

Katherine Abramski, Salvatore Citraro, Luigi Lombardi +2

Large language models are becoming increasingly integrated into our lives. Hence, it is important to understand the biases present in their outputs in order to avoid perpetuating h…

cs.CL20231 cited

Towards hypergraph cognitive networks as feature-rich models of knowledge

Salvatore Citraro, Simon De Deyne, Massimo Stella +1

Semantic networks provide a useful tool to understand how related concepts are retrieved from memory. However, most current network approaches use pairwise links to represent memor…

cs.SI2023

Attributed Stream Hypergraphs: temporal modeling of node-attributed high-order interactions

Andrea Failla, Salvatore Citraro, Giulio Rossetti

Recent advances in network science have resulted in two distinct research directions aimed at augmenting and enhancing representations for complex networks. The first direction, th…