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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 ISSN 1932-6203.

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Official URL: http://dx.doi.org/10.1371/journal.pone.0199845

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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, Engineering and Medicine > 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:
DateEvent
28 June 2018Published
14 June 2018Accepted
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 (Creative Commons)
Date of first compliant deposit: 4 October 2018
Date of first compliant Open Access: 4 October 2018
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
1500472, Influence Spread in Social Networks with Dynamic Topologies[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
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