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Using Generalized Annotated Programs to Solve Social Network Optimization Problems

Authors Paulo Shakarian, V.S. Subrahmanian, Maria Luisa Sapino



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Paulo Shakarian
V.S. Subrahmanian
Maria Luisa Sapino

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Paulo Shakarian, V.S. Subrahmanian, and Maria Luisa Sapino. Using Generalized Annotated Programs to Solve Social Network Optimization Problems. In Technical Communications of the 26th International Conference on Logic Programming. Leibniz International Proceedings in Informatics (LIPIcs), Volume 7, pp. 182-191, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2010)
https://doi.org/10.4230/LIPIcs.ICLP.2010.182

Abstract

Reasoning about social networks (labeled, directed, weighted graphs) is becoming increasingly important and there are now models of how certain phenomena (e.g. adoption of products/services by consumers, spread of a given disease) "diffuse" through the network. Some of these diffusion models can be expressed via generalized annotated programs (GAPs). In this paper, we consider the following problem: suppose we have a given goal to achieve (e.g. maximize the expected number of adoptees of a product or minimize the spread of a disease) and suppose we have limited resources to use in trying to achieve the goal (e.g. give out a few free plans, provide medication to key people in the SN) - how should these resources be used so that we optimize a given objective function related to the goal? We define a class of social network optimization problems (SNOPs) that supports this type of reasoning. We formalize and study the complexity of SNOPs and show how they can be used in conjunction with existing economic and disease diffusion models.
Keywords
  • Annotated logic programming
  • optimization queries
  • social networks

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