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Controllability of social networks and the strategic use of random information

BACKGROUND: This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender...

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Autores principales: Cremonini, Marco, Casamassima, Francesca
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732623/
https://www.ncbi.nlm.nih.gov/pubmed/29266124
http://dx.doi.org/10.1186/s40649-017-0046-2
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author Cremonini, Marco
Casamassima, Francesca
author_facet Cremonini, Marco
Casamassima, Francesca
author_sort Cremonini, Marco
collection PubMed
description BACKGROUND: This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. METHODS: Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network and considers two well-known strategies for influencing social contexts: One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad hoc metrics which are defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. RESULTS: The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills. CONCLUSIONS: These findings support our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable.
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spelling pubmed-57326232017-12-18 Controllability of social networks and the strategic use of random information Cremonini, Marco Casamassima, Francesca Comput Soc Netw Research BACKGROUND: This work is aimed at studying realistic social control strategies for social networks based on the introduction of random information into the state of selected driver agents. Deliberately exposing selected agents to random information is a technique already experimented in recommender systems or search engines, and represents one of the few options for influencing the behavior of a social context that could be accepted as ethical, could be fully disclosed to members, and does not involve the use of force or of deception. METHODS: Our research is based on a model of knowledge diffusion applied to a time-varying adaptive network and considers two well-known strategies for influencing social contexts: One is the selection of few influencers for manipulating their actions in order to drive the whole network to a certain behavior; the other, instead, drives the network behavior acting on the state of a large subset of ordinary, scarcely influencing users. The two approaches have been studied in terms of network and diffusion effects. The network effect is analyzed through the changes induced on network average degree and clustering coefficient, while the diffusion effect is based on two ad hoc metrics which are defined to measure the degree of knowledge diffusion and skill level, as well as the polarization of agent interests. RESULTS: The results, obtained through simulations on synthetic networks, show a rich dynamics and strong effects on the communication structure and on the distribution of knowledge and skills. CONCLUSIONS: These findings support our hypothesis that the strategic use of random information could represent a realistic approach to social network controllability, and that with both strategies, in principle, the control effect could be remarkable. Springer International Publishing 2017-10-13 2017 /pmc/articles/PMC5732623/ /pubmed/29266124 http://dx.doi.org/10.1186/s40649-017-0046-2 Text en © The Author(s) 2017 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Cremonini, Marco
Casamassima, Francesca
Controllability of social networks and the strategic use of random information
title Controllability of social networks and the strategic use of random information
title_full Controllability of social networks and the strategic use of random information
title_fullStr Controllability of social networks and the strategic use of random information
title_full_unstemmed Controllability of social networks and the strategic use of random information
title_short Controllability of social networks and the strategic use of random information
title_sort controllability of social networks and the strategic use of random information
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5732623/
https://www.ncbi.nlm.nih.gov/pubmed/29266124
http://dx.doi.org/10.1186/s40649-017-0046-2
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