Research of Social Processes by Means of the Theory of Self-Organized Criticality

Жуков, Д С; Lyamin, Sergey K.

doi:10.20310/1819-8813-2015-10-11-194-203

Cited by 2 publications

(5 citation statements)

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“…Данное исследование произведено в русле наших многолетних усилий по изучению эффектов СОК в социальных и политических системах. Соответствующие подходы и методологию мы детально рассмотрели в наших предшествующих публикациях [5]. Здесь обозначим ключевые положения теории СОК (и её инструментария), которые, полагаем, обуславливают её эффективность в фиксации, описании и объяснении феноменов, которые являются предметом данного исследовании.…”

Section: подход и инструментарийunclassified

“…Вес связи определён, соответственно, как количество совпадающих пользователей. «Действительно, если два сообщества имеют достаточно большое количество общих членов, то следует предположить, что для таких сообществ характерен интенсивный обмен сообщениями: мнениями, оценками, новостями и пр.» [5].…”

Section: картографирование сетиunclassified

“…Высокая вовлеченность в этой работе определена как «такое состояние участников сетевых сообществ, в котором участники проявляют повышенную готовность воспринимать и распространять сетевые политические сообщения (месседжи), опубликованные в сообществе, а также формировать свои оценки текущей политической ситуации, менять своё мнение и действовать (как в виртуальной реальности, так и на улицах) под воздействием таковых сообщений. Для политических сообществ сильная вовлеченность, как правило, означает и высокую политическую мобилизацию участников» [5].…”

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“…Следовательно, обнаружение 1/f-шума может быть использовано в ряде случаев для идентификации мобилизованных сообществ. Инструментарий теории СОК, поэтому, весьма удобен для мониторинга состояний сетевых сообществ» [5].…”

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Signature of rebellion: how SOC theory helps to detect signs of protest mobilization on the web

Zhukov

2022

Journal of Political Research

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The purpose of this study is to detect signs of political mobilization in social networks during the period of intensification of internal political struggle (including street actions of the opposition) at the beginning of 2021 in Russia. This study suggests a new quantitative indicator to reveal online communities (networks) characterized by strong user engagement and high level of political mobilization. VK-communities were mapped and analyzed in order to demonstrate the capability of this tool and determine levels of mobilization. The hypothesis of the study was that mobilized communities are able to turn virtual grievances into street protests. The object of study is a set (cluster) of related protest VK-communities (groups/hubs) through which messages from the most influential information donors are brought to public notice on the Internet. The proposed indicator for the calculation of mobilization level is based on the theory of self-organized criticality (SOC). The theory of SOC was initially created to describe a broad class of natural science phenomena, yet it has recently made its way into humanities and social sciences. Timeline of work: from January 10 to April 30, 2021. It was found that some groups (about 10%) in the considered cluster had a high mobilization index during this period. Many of the mobilized groups were very influential: they were both large-scale information donors and highly specialized protest communities. The practical significance of this study lies in improving the methods of monitoring network activity to identify groups that can influence the behavior of their members (both online and on the streets). This study also has theoretical significance related to the accumulation of knowledge about SOC effects in social systems.

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Section: подход и инструментарийunclassified

Section: картографирование сетиunclassified

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Signature of rebellion: how SOC theory helps to detect signs of protest mobilization on the web

Zhukov

2022

Journal of Political Research

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“…Recently, numerous evidences of self-organization of real-world systems of various origins to the edge of a phase transition have been obtained (e.g., see papers [5,6]). Tus, SOC is a characteristic of social interaction networks (e.g., see papers [7][8][9]) and online social networks (e.g., see papers [10][11][12][13][14][15]) such as Twitter. SOB is a characteristic of the brain (e.g., see the paper [16]).…”

Section: Introductionmentioning

confidence: 99%

Twitter Self-Organization to the Edge of a Phase Transition: Discrete-Time Model and Effective Early Warning Signals in Phase Space

Dmitriev,

Lebedev,

Kornilov

et al. 2023

Complexity

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Many real-world systems of various origins are capable of self-organization to the edge of a phase transition, characterized by avalanche-like behavior. Therefore, it is important, by observing the behavior of early warning measures for dynamical series generated by systems, to timely see the early warning signals (precursors) of such self-organization and, if necessary, take preventive measures. To date, convincing evidence of self-organization to the edge of a phase transition has been obtained, but no effective precursors for this self-organization have been found. This research explores precursors for the Twitter self-organization based on the analysis of the behavior of measures directly related to the critical slowdown of the network and measures of the phase space reconstructed by the Takens method for the series of the number of network users creating avalanches of retweets in the network, corresponding to the three debates of the 2016 United States Presidential Election. We hydrated the relevant Tweet IDs, which were obtained from the Harvard Dataverse using the Social Feed Manager, to form this series. Preliminarily, we explore the potential of measures for early detection of self-organization of sandpile cellular automata as systems with Twitter-equivalent self-organization mechanisms. The equivalence is justified in the proposed discrete-time model for Twitter self-organization to the edge of a phase transition. It is found that there are more moments of the Twitter self-organization than the moments of time when debates started, and Twitter stays at the edge of a phase transition longer than the debate lasts. The effective measures, as the measures with the lowest number of false early warning signals, among all studied measures and for all studied systems, are dispersion and correlation dimension. Obtained results are practically important in the design and implementation of early warning systems for the systems with similar mechanisms for sandpile cellular automata self-organization to the edge of a phase transition.

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Research of Social Processes by Means of the Theory of Self-Organized Criticality

Cited by 2 publications

References 0 publications

Signature of rebellion: how SOC theory helps to detect signs of protest mobilization on the web

Signature of rebellion: how SOC theory helps to detect signs of protest mobilization on the web

Twitter Self-Organization to the Edge of a Phase Transition: Discrete-Time Model and Effective Early Warning Signals in Phase Space

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