Abstract
The propagation of concepts through a population of agents can be modelled as a cascade of influence spread from an initial set of individuals. In real-world environments there may be many concepts spreading and interacting, and we may not be able to directly control the target concept we wish to manipulate, requiring indirect manipulation through a secondary controllable concept. Previous work on influence spread typically assumes that we have full knowledge of a network, which may not be the case. In this paper, we investigate indirect influence manipulation when we can only observe a sample of the full network. We propose a heuristic, known as Target Degree, for selecting seed nodes for a secondary controllable concept that uses the limited information available in a partially observable environment to indirectly manipulate the target concept. Target degree is shown to be effective in synthetic small-world networks and in real-world networks when the controllable concept is introduced after the target concept.
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Notes
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These networks are samples of full social networks, but for the purposes of this paper we treat them as the complete network.
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Archbold, J., Griffiths, N. (2019). Indirect Influence Manipulation with Partial Observability. In: Davidsson, P., Verhagen, H. (eds) Multi-Agent-Based Simulation XIX. MABS 2018. Lecture Notes in Computer Science(), vol 11463. Springer, Cham. https://doi.org/10.1007/978-3-030-22270-3_3
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DOI: https://doi.org/10.1007/978-3-030-22270-3_3
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