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Manipulating concept spread using concept relationships
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Archbold, James and Griffiths, Nathan (2018) Manipulating concept spread using concept relationships. PLoS One, 13 (6). e0199845. doi:10.1371/journal.pone.0199845
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Official URL: http://dx.doi.org/10.1371/journal.pone.0199845
Abstract
The propagation of concepts in a population of agents is a form of influence spread, which can be modelled as a cascade from a set of initially activated individuals. The study of such influence cascades, in particular the identification of influential individuals, has a wide range of applications including epidemic control, viral marketing and the study of social norms. In real-world environments there may be many concepts spreading and interacting. These interactions can affect the spread of a given concept, either boosting it and allowing it to spread further, or inhibiting it and limiting its capability to spread. Previous work does not consider how the interactions between concepts affect concept spread. Taking concept interactions into consideration allows for indirect concept manipulation, meaning that we can affect concepts we are not able to directly control. In this paper, we consider the problem of indirect concept manipulation, and propose heuristics for indirectly boosting or inhibiting concept spread in environments where concepts interact. We define a framework that allows for the interactions between any number of concepts to be represented, and present a heuristic that aims to identify important influence paths for a given target concept in order to manipulate its spread. We compare the performance of this heuristic, called maximum probable gain, against established heuristics for manipulating influence spread.
| Item Type: | Journal Article | ||||||
|---|---|---|---|---|---|---|---|
| Subjects: | Q Science > QA Mathematics > QA76 Electronic computers. Computer science. Computer software | ||||||
| Divisions: | Faculty of Science > Computer Science | ||||||
| SWORD Depositor: | Library Publications Router | ||||||
| Library of Congress Subject Headings (LCSH): | Heuristic algorithms, Epidemics -- Mathematical models, Marketing -- Mathematical models, Social norms -- Mathematical models | ||||||
| Journal or Publication Title: | PLoS One | ||||||
| Publisher: | Public Library of Science | ||||||
| ISSN: | 1932-6203 | ||||||
| Official Date: | 28 June 2018 | ||||||
| Dates: |
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| Date of first compliant deposit: | 4 October 2018 | ||||||
| Date of first compliant Open Access: | 4 October 2018 | ||||||
| Volume: | 13 | ||||||
| Number: | 6 | ||||||
| Article Number: | e0199845 | ||||||
| DOI: | 10.1371/journal.pone.0199845 | ||||||
| Status: | Peer Reviewed | ||||||
| Publication Status: | Published | ||||||
| Access rights to Published version: | Open Access | ||||||
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