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**:** 2019
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**:** 79
**:** .., .., .., .. // . 79. .: , 2019. .27-64. URL: https://doi.org/10.25728/ubs.2019.79.2

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** (.):** marketing, network analysis and forecasting models, control of target audience

**:** . . , , . , R. . . , . 10-15 . : , , , . .

** (.):** Some networks analysis and forecasting models are considered in the paper relative to marketing. A brief survey of the control and influence models on social networks is presented. Namely, the problems include determination of the strong subgroups and satellites, calculation of quantitative characteristics of the network, determination of the final opinions of the members of the target audience based on their initial opinions and mutual interactions. For the solution of the forecasting problem an original algorithm is developed and implemented by means of the programming language R. The algorithm is described in details and considers a specific case of a strongly connected digraph and the general case. The complexity of the algorithm is estimated. Other named problems can be solved by embedded functions of the language that is illustrated by test examples together with the results of the authors' algorithm. The model examples use influence digraphs with 10-15 and more than 100 vertices. Such closeness measures as degree centrality, closeness centrality, and betweenness centrality are calculated for the model example, their interpretation is given. Solution of the analysis and forecasting problems essentially facilitates the problem of control of the opinions of target audience in marketing. The directions of future research in building and analysis of the models of opinion control in marketing are outlined.

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