Opinion Optimization for Two Different Social Objectives: Combinatorial Algorithms and Linear Program Rounding

Po An Chen*, Yi Le Chen, Wei Lo

*Corresponding author for this work

Research output: Contribution to journalEditorial

Abstract

In this paper, we aim to optimize the two different social objectives of opinion optimization at equilibrium by controlling some individuals. This is usually called “Stackelberg games”, in which a centralized authority is allowed to assign the strategies to a subset of individuals. The Stackelberg strategies of the centralized authority are the algorithms to select a subset of individuals and decide the actions for them in order to palliate the cost caused by the selfish behavior of the uncontrolled individuals. We give some combinatoral algorithms and linear program rounding algorithms as Stackelberg strategies for approximately optimizing the objective of utilitarian social cost (on special cases) and the objective of total expressed opinion (on general directed graphs), respectively.

Original languageEnglish
Pages (from-to)217-230
Number of pages14
JournalJournal of Information Science and Engineering
Volume40
Issue number2
DOIs
StatePublished - Mar 2024

Keywords

  • combinatorial algorithms
  • linear program rounding
  • opinion optimization
  • randomized algorithms
  • Stackelberg strategies

Fingerprint

Dive into the research topics of 'Opinion Optimization for Two Different Social Objectives: Combinatorial Algorithms and Linear Program Rounding'. Together they form a unique fingerprint.

Cite this