TY - GEN

T1 - Using generalized annotated programs to solve social network optimization problems

AU - Shakarian, Paulo

AU - Subrahmanian, V. S.

AU - Sapino, Maria Luisa

PY - 2010

Y1 - 2010

N2 - Reasoning about social networks (labeled, directed, weighted graphs) is be- coming increasingly important and there are now models of how certain phenomena (e.g. adoption of products/services by consumers, spread of a given disease) "diffuuse" 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.

AB - Reasoning about social networks (labeled, directed, weighted graphs) is be- coming increasingly important and there are now models of how certain phenomena (e.g. adoption of products/services by consumers, spread of a given disease) "diffuuse" 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.

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U2 - 10.4230/LIPIcs.ICLP.2010.182

DO - 10.4230/LIPIcs.ICLP.2010.182

M3 - Conference contribution

AN - SCOPUS:84880202202

SN - 9783939897170

T3 - Leibniz International Proceedings in Informatics, LIPIcs

SP - 182

EP - 191

BT - Technical Communications of the 26th International Conference on Logic Programming, ICLP 2010

T2 - 26th International Conference on Logic Programming, ICLP 2010

Y2 - 16 July 2010 through 19 July 2010

ER -