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Concept spread results for 2 concept environments

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Archbold, James (2017) Concept spread results for 2 concept environments. [Dataset]

Research output not available from this repository, contact author.
Official URL: https://doi.org/10.5281/zenodo.1007743

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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: Dataset
Subjects: B Philosophy. Psychology. Religion > BD Speculative Philosophy
H Social Sciences > HM Sociology
Divisions: Faculty of Science > Computer Science
Type of Data: Modelling data
Library of Congress Subject Headings (LCSH): Concepts, Influence (Psychology), Social norms -- Mathematical models
Publisher: Zenodo
Official Date: 10 October 2017
Dates:
DateEvent
10 October 2017Published
Status: Not Peer Reviewed
Publication Status: Published
Media of Output: .txt
Access rights to Published version: Open Access
Copyright Holders: University of Warwick
Description:

Data record consists of 2 zip archives, containing raw data for multiple concepts spreading within a network.
Files follow this format:
10 line preamble listing the parameters of the run/runs
Dashed line break
"Run #" where # is the current run number
Time in milliseconds of start
"Timestep n" - n starting at 0
"Infections [conceptType]0: [Number of infected nodes in current time step for target]"
"Infections [conceptType]1: [Number of infected nodes in current time step for controllable]"
These three lines repeat for each time step. Before a final result heading, with the final infections.
Time in milliseconds that run ended.
Dashed line divider.
Then, if the file contains a single run the file will end or, if it contains multiple runs, will proceed to the next run.

RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
1500472[EPSRC] Engineering and Physical Sciences Research Councilhttp://dx.doi.org/10.13039/501100000266
Related URLs:
  • http://wrap.warwick.ac.uk/106628/
  • Other
Contributors:
ContributionNameContributor ID
Contact PersonArchbold, James65498

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