Proportional Selection in Networks: Balancing Influence and Diversity
A new computer science paper proposes methods for selecting representative nodes from networks while balancing influence and diversity. The research addresses the challenge of choosing k nodes that are both influential and proportionally reflect the network's diversity. Two approaches are introduced, analyzed theoretically, and validated through experiments. The work is categorized under Computer Science and Game Theory and was submitted to arXiv on February 5, 2025.
Key facts
- The paper addresses selecting k representative nodes from a network.
- Two objectives: identifying most influential nodes and ensuring proportional diversity.
- Two approaches are proposed and analyzed theoretically.
- Effectiveness demonstrated through experiments.
- Submitted to arXiv on February 5, 2025.
- Categorized under Computer Science and Game Theory.
Entities
Institutions
- arXiv