Mathematical Model of Dissemination of Informational and Psychological Influences in the Social Network Segment

Ulichev, Oleksandr

doi:10.32515/2409-9392.2018.31.165-174

Cited by 3 publications

(5 citation statements)

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“…As noted by Ulichev [11], informational influences are an effective tool for manipulating people; therefore, the fact of using Internet services for the implementation of destructive informational influences determines the development of methods and means of resisting these influences. For effective counteraction, it is necessary to study the nature of such influences and the necessary tools for their analysis.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

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Methodology of monitoring negative psychological influences in online media

Vakaliuk¹,

Pilkevych²,

Fedorchuk³

et al. 2022

Educ. Technol. Q.

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The experience of the military aggression of the Russian Federation against Ukraine has shown the relevance and necessity of understanding the problems of moral and psychological support in the Armed Forces of Ukraine in modern conditions. The problem of constant misinformation of the population, the spread of propaganda and the implementation of destructive psychological influence in the interests of the enemy is very sensitive. The simplest tool for distribution misinformation is the Internet (its easy access and wide popularity). The goal of the article is to develop a methodology for monitoring negative psychological influences in online media. The basis of develop methodology is the build a mathematical model using a 4th order polynomial trendline. To determine the number of text messages that were simultaneously processed in statistical analysis, the Hurst exponent was applied. Indicators of negative psychological influences in text messages are selected. Statistical observation is carried out at the expense of a database with text messages from online media. The coefficients of the polynomial regression model are calculated using the least squares method for using a spreadsheet processor Microsoft Excel, or by solving a system of linear algebraic equations using Cramer's method. It has been proved that the developed mathematical model for monitoring negative psychological influences is adequate over the time interval under study. Due to the developed methodology for monitoring negative psychological influences in online media, it is possible to mathematically describe the process of the influence of text messages on a person. The mathematical model underlying the methodology can be used not only at the monitoring stage, but also at the stage of counteracting destructive psychological effects, as well as for the implementation of preventive measures to prevent the spread of such effects by taking into account the frequency and common ways of spreading negative psychological effects in text messages online media. It should be noted that the developed methodology can be used to automate online media monitoring in order to timely identify information threats to military command and control bodies and the personnel of the Armed Forces of Ukraine in the context of ensuring the information security of the state.

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Section: Theoretical Backgroundmentioning

confidence: 99%

“…Ulichev [11] considers a mathematical model of the dissemination of information and psychological influences in a segment of a social network. The network structure is presented as a graph, and the information dissemination is presented as an iterative process.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Methodology of monitoring negative psychological influences in online media

Vakaliuk¹,

Pilkevych²,

Fedorchuk³

et al. 2022

Educ. Technol. Q.

View full text Add to dashboard Cite

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“…When choosing parameters; the node characteristics, it is necessary to try to reduce their quantity, while not losing the adequacy of the model, the model should give results close to reality. In Ulichev (2018) the model, a node (social network user) is described by the following characteristics: where (Act) Active-user activity, the active dialog quantity (calls to other users) during one iteration of the model; (R) Reputation-user reputation, the influence of the message, the persuasion power; (Op) Opposite-information resistance, criticality concerning the idea that spreads; (I) Involvement-the degree of involvement in the idea, trust level; Vj i many contacts, nodes with which there is information exchange, node V i .…”

Section: Preliminariesmentioning

confidence: 99%

“…As reported in Ulichev (2018), the behavioral strategy (let's conditionally call it "Bush") can be described:…”

Section: Preliminariesmentioning

confidence: 99%

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Modeling strategies for information influence dissemination in social networks

Al-Oraiqat¹,

Ulichev

Meleshko

et al. 2021

J Ambient Intell Human Comput

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This research presents a thorough study of the strategies deployed for information dissemination on social networks. The strategies are modeled for identifying factors proving pivotal in influencing public opinions. The public is categorized into active and passive participants to discuss the study of these strategies for disseminating informational pieces such as images, sketches, text, and so on social networks, based on computer modeling of the social network structure alongside modeling of the behavior of network users. The objective of this research is to benchmark the proposed model on the effectiveness of information dissemination strategies that can be proposed to spread informational influences on social networks. As a rule, "Opinion Leaders" in the purpose network sectors are used to spread information on social media among the largest number of users in the least amount of time. Experiments have proved the effectiveness of the information dissemination model using "Opinion Leaders", as well as the efficiency of the methods of information dissemination for different winning structural positions in a social network. Experiments have also confirmed the high effectiveness in attracting "Opinion Leaders" to the dissemination processes.

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Automation of Information Materials Distribution in Social Networks

Pilkevych,

Savchuk,

Pavlenko

et al. 2024

Проблеми Створення, Випробування, Застосування Та Експлуатації Складних Інформаційних Систем

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In order consider the process of distributing information materials among a specific target audience in the course of conducting psychological operations by Joint Special Operations Command of the Armed Forces of Ukraine to increase efficiency in using time resources by relevant officials in case information materials are distributed. Results of analysis of available types or accounts, considered in view on their purpose and possibilities to distribute influence materials, show that the choice in favour of a particular type an account determines the method a publication is made and the further procedure for interacting with the audience. This article examines the key aspects related to effective dissemination on social media, including choosing methods of publication, types of accounts, and optimal settings for the dissemination process. Particular attention is focused on finding the most suitable groups to achieve maximum coverage by the target audience, as well as on taking into account activity and interests of its members. It is established that successful dissemination the influence materials depends not only on their content, but also on the right choice of tools and strategies for dissemination. On basis of the carried out research, an algorithm for optimal dissemination information materials in social networks has been developed to achieve greatest impact on target audience. It is assumed that development a special software based on proposed algorithm for optimal distribution of influence materials in social networks will increase efficiency of information and analytical activities in special units by: determining a list of influence channels for target audience, automating the processes of distribution an influence materials and optimizing management of the database of accounts in social networks simultaneously.

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Mathematical Model of Dissemination of Informational and Psychological Influences in the Social Network Segment

Cited by 3 publications

References 0 publications

Methodology of monitoring negative psychological influences in online media

Methodology of monitoring negative psychological influences in online media

Modeling strategies for information influence dissemination in social networks

Automation of Information Materials Distribution in Social Networks

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