The IIT-CNR Ubiquitous Internet Unit is seeking talented researchers at the postdoctoral level to work on a research topic: Signed Graphs for Online Social Networks: Data-Driven Characterization, Temporal Dynamics, and Applications.
The position is open at the postdoctoral level, with the research direction adaptable to the applicant's expertise and interests.
Candidates with strong analytical and computational skills, as well as an interest in social network analysis, AI/ML, and data-driven research, are encouraged to apply.
Candidate Profile:
* PhD in Computer Science, Physics (complex networks), or Mathematics.
* Strong programming skills for data collection, processing, and model training.
* Experience or interest in interdisciplinary research, such as computational social science.
We aim to fill the gap in reliable ground truth datasets by designing and deploying new methodologies to collect signed graphs and use them to train AI/ML models and improve social network analysis.
Research Topic:
Social relationships are shaped by multiple factors, including frequency of interaction, trust, and emotional connection. Recent studies have shifted toward more qualitative aspects of relationships, moving beyond mere interaction counts to understanding the nature of social connections.
One of the most widely used ways to encode the quality of relationships is by assigning a positive or negative sign to them. Positive relationships often represent trust, homophily, or mutual support. Negative relationships may indicate conflict, distrust, or rivalry.
Funding and Partnerships:
The activities of this topic will be supported by FAIR: Extended Partnership on Artificial Intelligence and ICSC: National Research Centre for High-Performance Computing, Big Data, and Quantum Computing.