Multi-relational Graph Modeling and Learning for Large-Scale Social Network Analysis
Scientific-Disciplinary Group
01/INFO-01 - Informatics
Description
The project proposes a theoretical andmethodological study on multi-relational modeling of large-scale social networks using graph representationlearning techniques. The objective is to investigate how different interaction types (e.g., user relations, contentusage, temporal dynamics) can be modeled as distinct relational views of the same network and integrated into aunified framework. The research relies on a real-world dataset covering the entire Italian Twitter sphere in 2022and aims to evaluate modular Graph Neural Network architectures for scalable and interpretable noderepresentation learning. Applications to link prediction, community detection, and emerging social dynamicsanalysis will be explored
Job posting website
Number of positions
1
Funding body
Università degli Studi di Roma Tor Vergata - Dipartimento di Ingegneria dell'Impresa Mario Lucertini
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