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Opinion Manipulation in Social Networks

In this work, we are interested in finding the most efficient use of a budget to promote an opinion by paying agents within a group to supplant their true opinions. We model opinions as continuous scalars ranging from 0 to 1 with 1 (0) representing extremely positive (negative) opinion. We focus on asymmetric confidence between agents. The iterative update of an agent corresponds to the best response to other agents' actions. The resulting confidence matrix can be seen as an equivalent Markov chain. We provide simple and efficient algorithms to solve this problem and we show through an example how to solve the stated problem in practice.

preprint2016arXivOpen access
Alonso Silva
Social and Information NetworksComputer Science and Game Theory
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Open access1 author2 topics
Imported metadata coverageMissing code, dataset, citation and institution fields are tracked without dominating the paper.Details
Citations: 0Reviews: 0Saves: 0Code: not linkedDataset: not linkedInstitutions: 0

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Alonso Silva

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