Social Networks: Models of Information Influence, Control and Confrontation

Chkhartishvili, Alexander G.; Gubanov, Dmitry; Novikov, Dmitry A.

doi:10.1007/978-3-030-05429-8

Cited by 77 publications

(21 citation statements)

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“…The models of finding a consensus are close to the models of informational influence on population and information control models (see, e.g., papers [2,3] and books [4,5]). A model of opinion dynamics with two principals or centers of influence is presented in [6], in which the conditions of existence of the limit opinions are obtained for a given matrix of influences.…”

Section: Introductionmentioning

confidence: 62%

The Euler-Equation Approach in Average-Oriented Opinion Dynamics

Мазалов

Parilina

2020

Mathematics

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We consider the models of average-oriented opinion dynamics. An opinion about an event is distributed among the agents of a social network. There are an optimization problem and two game-theoretical models when players as centers of influence aim to make the opinions of the agents closer to the target ones in a finite time horizon minimizing their costs. The optimization problem and the games of competition for the agents’ opinion are linear-quadratic and solved using the Euler-equation approach. The optimal strategies for optimization problem and the Nash equilibria in the open-loop strategies for the games are found. Numerical simulations demonstrate theoretical results.

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Section: Introductionmentioning

confidence: 62%

The Euler-Equation Approach in Average-Oriented Opinion Dynamics

Мазалов

Parilina

2020

Mathematics

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“…A detailed analysis of influence models and some formulations of control models were given in the monograph [25]. A closest approach to the one developed below was presented in [26,27], where linear-quadratic game-theoretic models were constructed and investigated on a network with two influence nodes.…”

Section: Introductionmentioning

confidence: 99%

Modeling and Simulation of Impact and Control in Social Networks with Application to Marketing

Agieva

Korolev²,

Ougolnitsky

2020

Mathematics

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The problems of social networks analysis and calculation of the resulting opinions of network agents are considered. Algorithms for identifying strong subgroups and satellites as well as for calculating some quantitative characteristics of a network are implemented by the R programming language and tested on model examples. A new algorithm for calculating the resulting opinions of agents is developed by the R toolkit and tested on model examples. It is important that control actions that exert impact to the opinions should be applied exclusively to the members of strong subgroups (opinion leaders of a target audience), since they fully determine the stable resulting opinions of all network members. This approach allows saving control resources without significantly affecting its efficiency. Much attention is paid to the original models of optimal control (single subject) and conflict control (several competing subjects) under the assumption that the members of strong subgroups (opinion leaders) are already identified at the previous stage of network analysis. Models of optimal opinion control on networks are constructed and investigated by computer simulations using the author’s method of qualitatively representative scenarios. Differential game-based models of opinion control on networks with budget constraints in the form of equalities and inequalities are constructed and analytically investigated. All used notions, approaches and results of this paper are interpreted in terms of marketing problems.

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“…The reviews can be found in [3]- [4]. Along with the models of influence, there are also models of opinion control in social networks [6]. In this case there are one or several external control agents that exert influence on the opinions of basic network agents in their interests.…”

mentioning

confidence: 99%

“…Formally, the strong subgroups are the strong components of a network which belong to the vertex base of its condensation [13]. Thus, the first stage of analysis of a network consists in its segmentation on strong subgroups and satellites [6] as well as calculation of additional quantitative characteristics of the members of strong subgroups [2]. In the second stage the problems of optimal and conflict (game theoretic) opinion control are solved.…”

mentioning

confidence: 99%

Optimal resource allocation in the difference and differential Stackelberg games on marketing networks

Korolev

Ougolnitsky²

2020

Journal of Dynamics &Amp; Games

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We consider difference and differential Stackelberg game theoretic models with several followers of opinion control in marketing networks. It is assumed that in the stage of analysis of the network its opinion leaders have already been found and are the only objects of control. The leading player determines the marketing budgets of the followers by resource allocation. In the basic version of the models both the leader and the followers maximize the summary opinions of the network agents. In the second version the leader has a target value of the summary opinion. In all four models we have found the Stackelberg equilibrium and the respective payoffs of the players analytically. It is shown that the hierarchical control system is ideally compatible in all cases.

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Social Networks: Models of Information Influence, Control and Confrontation

Cited by 77 publications

References 0 publications

The Euler-Equation Approach in Average-Oriented Opinion Dynamics

The Euler-Equation Approach in Average-Oriented Opinion Dynamics

Modeling and Simulation of Impact and Control in Social Networks with Application to Marketing

Optimal resource allocation in the difference and differential Stackelberg games on marketing networks

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