Self‐Organized Criticality on Twitter: Phenomenological Theory and Empirical Investigation Based on Data Analysis Results

Abstract

Recently, there has been an increasing number of empirical evidence supporting the hypothesis that spread of avalanches of microposts on social networks, such as Twitter, is associated with some sociopolitical events. Typical examples of such events are political elections and protest movements. Inspired by this phenomenon, we built a phenomenological model that describes Twitter’s self-organization in a critical state. An external manifestation of this condition is the spread of avalanches of microposts on the network. The model is based on a fractional three-parameter self-organization scheme with stochastic sources. It is shown that the adiabatic mode of self-organization in a critical state is determined by the intensive coordinated action of a relatively small number of network users. To identify the critical states of the network and to verify the model, we have proposed a spectrum of three scaling indicators of the observed time series of microposts.

Modeling latent infection transmissions through biosocial stochastic dynamics

“…Some prominent examples are the emotion spreading in online social networks [ 5 – 8 ], opinion dynamics [ 9 ], and constructive engagement for the collective knowledge creation [ 10 ]. A detailed analysis of empirical data of human activity online and related theoretical modelling [ 6 , 11 , 12 ] provided evidence that the prominent dynamical mechanisms enabling these collective phenomena lie in the self-organised criticality [ 13 – 15 ]. The appropriate agent-based modeling of these social phenomena [ 16 ] includes the individual emotional [ 5 , 6 ] and cognitive properties [ 10 ] of the interacting agents.…”

Egg parasitoids of Arboridia apicalis (Nawa, 1913) (Hemiptera, Cicadellidae), a leafhopper pest of grapevines in Japan, with description of a new species of Anagrus Haliday, 1833 (Hymenoptera, Mymaridae)

“…1b-f ); also, when abundant, particularly in the organic vineyards on Honshu Island, adult A. apicalis are a significant nuisance to the pickers at harvest by getting into peoples' faces. Both A. apicalis and A. suzukii are native to the Eastern Palaearctic and Northeastern Oriental regions, with more or less similar distributions: that of A. apicalis includes Japan (throughout), Korean Peninsula, Far East of Russia, mainland China and Taiwan (Guglielmino et al 2012;Li 2013, 2015;Oh et al 2015;Dmitriev 2019) while A. suzukii occurs in Japan (Honshu, Kyushu, and Shikoku Islands), Korean Peninsula, Far East of Russia, mainland China, and Taiwan (Oh et al 2015;Dmitriev 2019). Arboridia apicalis is a polyphagous leafhopper feeding on various deciduous trees and vines, such as cherry, grape, hawthorn, apple, pear, peach, mulberry, maple (Yamada 2003;Guglielmino et al 2012;Song and Li 2015;Dmitriev 2019).…”

“…Both A. apicalis and A. suzukii are native to the Eastern Palaearctic and Northeastern Oriental regions, with more or less similar distributions: that of A. apicalis includes Japan (throughout), Korean Peninsula, Far East of Russia, mainland China and Taiwan (Guglielmino et al 2012;Li 2013, 2015;Oh et al 2015;Dmitriev 2019) while A. suzukii occurs in Japan (Honshu, Kyushu, and Shikoku Islands), Korean Peninsula, Far East of Russia, mainland China, and Taiwan (Oh et al 2015;Dmitriev 2019). Arboridia apicalis is a polyphagous leafhopper feeding on various deciduous trees and vines, such as cherry, grape, hawthorn, apple, pear, peach, mulberry, maple (Yamada 2003;Guglielmino et al 2012;Song and Li 2015;Dmitriev 2019). The known host plants of A. suzukii, besides grape, are apple, pear, Manchurian cherry (Dmitriev 2019), and also Japanese chestnut; this leafhopper is a pest in the Japanese vineyards mainly in Kyushu Island, causing damage particularly to leaf edges whereas A. apicalis damages the entire leaf more uniformly (Yamada 2003, illustrated by Sakagami (2003).…”

“…Arboridia apicalis is a polyphagous leafhopper feeding on various deciduous trees and vines, such as cherry, grape, hawthorn, apple, pear, peach, mulberry, maple (Yamada 2003;Guglielmino et al 2012;Song and Li 2015;Dmitriev 2019). The known host plants of A. suzukii, besides grape, are apple, pear, Manchurian cherry (Dmitriev 2019), and also Japanese chestnut; this leafhopper is a pest in the Japanese vineyards mainly in Kyushu Island, causing damage particularly to leaf edges whereas A. apicalis damages the entire leaf more uniformly (Yamada 2003, illustrated by Sakagami (2003). Both species overwinter as adults in dropped leaves, weeds, cracks in bark, and under cover of buildings.…”

Modeling latent infection transmissions through biosocial stochastic dynamics

“…Some prominent examples are the emotion spreading in online social networks [5][6][7][8] , opinion dynamics 9 , and constructive engagement for the collective knowledge creation 10 . A detailed analysis of empirical data of human activity online and related theoretical modelling 6,11,12 provided evidence that the prominent dynamical mechanisms enabling these collec-tive phenomena lie in the self-organised criticality [13][14][15] . The appropriate agent-based modeling of these social phenomena 16 includes the individual emotional 5,6 and cognitive properties 10 of the interacting agents.…”