Collapse of an online social network: Burning social capital to create it?

Lőrincz, László; Koltai, Júlia; Győr, Anna Fruzsina; Takács, Károly

doi:10.1016/j.socnet.2018.11.004

Cited by 38 publications

(27 citation statements)

References 66 publications

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“…In previous studies, the data has demonstrated that the gravity law applies to the spatial structure of social ties 24 , that adoption rates correlate positively both with town size and with physical proximity to the original location 25 , that users central in the network churn the service after the users who are on the periphery of the network 26 , and that the cascade of churn follows a threshold rule 27 . Socio-economic outcomes such as local corruption risk 28 and income inequalities 29 have been also investigated with the use of iWiW data.…”

Section: Datamentioning

confidence: 99%

The role of geography in the complex diffusion of innovations

Lengyel

Bokányi

Clemente

et al. 2020

Sci Rep

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The urban–rural divide is increasing in modern societies calling for geographical extensions of social influence modelling. Improved understanding of innovation diffusion across locations and through social connections can provide us with new insights into the spread of information, technological progress and economic development. In this work, we analyze the spatial adoption dynamics of iWiW, an Online Social Network (OSN) in Hungary and uncover empirical features about the spatial adoption in social networks. During its entire life cycle from 2002 to 2012, iWiW reached up to 300 million friendship ties of 3 million users. We find that the number of adopters as a function of town population follows a scaling law that reveals a strongly concentrated early adoption in large towns and a less concentrated late adoption. We also discover a strengthening distance decay of spread over the life-cycle indicating high fraction of distant diffusion in early stages but the dominance of local diffusion in late stages. The spreading process is modelled within the Bass diffusion framework that enables us to compare the differential equation version with an agent-based version of the model run on the empirical network. Although both model versions can capture the macro trend of adoption, they have limited capacity to describe the observed trends of urban scaling and distance decay. We find, however that incorporating adoption thresholds, defined by the fraction of social connections that adopt a technology before the individual adopts, improves the network model fit to the urban scaling of early adopters. Controlling for the threshold distribution enables us to eliminate the bias induced by local network structure on predicting local adoption peaks. Finally, we show that geographical features such as distance from the innovation origin and town size influence prediction of adoption peak at local scales in all model specifications.

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Section: Datamentioning

confidence: 99%

The role of geography in the complex diffusion of innovations

Lengyel

Bokányi

Clemente

et al. 2020

Sci Rep

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“…Such situations may occur in power grids and transportation networks [27,28]. Another mechanism of cascading failures was identified in social networks in which a user who leaves the network may encourage some of his/her friends to leave the network too, possibly for joining a competing network [29,30].…”

Section: Network Contraction Processesmentioning

confidence: 99%

Convergence towards an Erdős-Rényi graph structure in network contraction processes

2019

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In a highly influential paper twenty years ago, Barabási and Albert [Science 286, 509 (1999)] showed that networks undergoing generic growth processes with preferential attachment evolve towards scale-free structures. In any finite system, the growth eventually stalls and is likely to be followed by a phase of network contraction due to node failures, attacks or epidemics. Using the master equation formulation and computer simulations we analyze the structural evolution of networks subjected to contraction processes via random, preferential and propagating node deletions. We show that the contracting networks converge towards an Erdős-Rényi network structure whose mean degree continues to decrease as the contraction proceeds. This is manifested by the convergence of the degree distribution towards a Poisson distribution and the loss of degree-degree correlations.

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“…A well-known reversal case would be the shifts in the popularity of different online social networks in the past ten years, such as Facebook's overtake of Myspace, and the collapse of iWiW [65,66]. Specifically, iWiW used to be the most popular online social network in Hungary and owed great competitive advantage before 2010, while subsequently Facebook joined the competition and achieved the dramatic reversal [67]. Considering the rapid evolutions of competitive industry or Internet products nowadays, the reversing condition in our work may shed light on designing effective competing strategies in a large range of real situations, such as spreading new ideas, promoting industrial products and doing marketing.…”

Section: Conclusion and Discussionmentioning

confidence: 99%

Homogeneity trend on social networks changes evolutionary advantage in competitive information diffusion

et al. 2020

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Competitive information diffusion on large-scale social networks reveals fundamental characteristics of rumor contagions and has profound influence on public opinion formation. There has been growing interest in exploring dynamical mechanisms of the competing evolutions recently. Nevertheless, the impacts of homogeneity trend, which determines powerful collective human behaviors, remains unclear. In this paper, we incorporate homogeneity trend into a modified competitive ignorant-spreader-ignorant rumor diffusion model with generalized population preference. Using microscopic Markov chain approach, we first derive the phase diagram of competing diffusion results on Erdös-Rényi graph and examine how competitive information spreads and evolves on social networks. We then explore the detailed effects of homogeneity trend, which is modeled by a rewiring mechanism. Results show that larger homogeneity trend promotes the formation of polarized 'echo chambers' and protects the disadvantaged information from extinction, which further changes or even reverses the evolutionary advantage, namely, the difference of stable proportions of the competitive information. However, the reversals may happen only when the initially disadvantaged information has stronger transmission ability, owning diffusion advantage over the other one. Our framework provides profound insight into competing dynamics with homogeneity trend, which may pave ways for further controlling misinformation and guiding public belief systems. Moreover, the reversing condition sheds light on designing effective competing strategies in many real scenarios.

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Collapse of an online social network: Burning social capital to create it?

Cited by 38 publications

References 66 publications

The role of geography in the complex diffusion of innovations

The role of geography in the complex diffusion of innovations

Convergence towards an Erdős-Rényi graph structure in network contraction processes

Homogeneity trend on social networks changes evolutionary advantage in competitive information diffusion

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