Friendship and mobility

Cho, Eunjoon; Myers, Seth A.; Leskovec, Jure

doi:10.1145/2020408.2020579

Cited by 2,206 publications

(256 citation statements)

References 27 publications

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“…Focusing on the SIRS model, in Figures 5(a) and 5(b) we present numerical simulations on two SF real networks. We consider in particular the location-based social network Gowalla [33] and the product co-purchasing network in Amazon website [34], possessing degree exponents smaller and larger than 3, respectively, Figure 5(c). According QMF theory, the thresholds for these networks are equal to the inverse of the largest eigenvalue of their adjacency matrix.…”

Section: Sirs Models On Real Networkmentioning

confidence: 99%

Collective versus hub activation of epidemic phases on networks

2016

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We consider a general criterion to discern the nature of the threshold in epidemic models on scale-free (SF) networks. Comparing the epidemic lifespan of the nodes with largest degrees with the infection time between them, we propose a general dual scenario, in which the epidemic transition is either ruled by a hub activation process, leading to a null threshold in the thermodynamic limit, or given by a collective activation process, corresponding to a standard phase transition with a finite threshold. We validate the proposed criterion applying it to different epidemic models, with waning immunity or heterogeneous infection rates in both synthetic and real SF networks. In particular, a waning immunity, irrespective of its strength, leads to collective activation with finite threshold in scale-free networks with large exponent, at odds with canonical theoretical approaches.

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Section: Sirs Models On Real Networkmentioning

confidence: 99%

Collective versus hub activation of epidemic phases on networks

2016

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“…However, prompt isolations can effectively contain epidemics in more realistic networks. Figures 7(a) and 7(b) show the Monte Carlo results for the two real networks: the sexual contact network between Brazilian prostitutes and sex buyers [27], and the friendship network of Gowalla users (Gowalla is a location-based social networking website where users share their locations by checking in) [28]. Since the data of sexual contact network collected by Rocha et al [27] constitute a time-ordered list, we consider a time-integrated network, where multiple edges between a node pair are accepted.…”

Section: Case Of Real Networkmentioning

confidence: 99%

Efficiency of prompt quarantine measures on a susceptible-infected-removed model in networks

Hasegawa

Nemoto

2017

Phys. Rev. E

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This study focuses on investigating the manner in which a prompt quarantine measure suppresses epidemics in networks. A simple and ideal quarantine measure is considered in which an individual is detected with a probability immediately after it becomes infected and the detected one and its neighbors are promptly isolated. The efficiency of this quarantine in suppressing a susceptible-infected-removed (SIR) model is tested in random graphs and uncorrelated scale-free networks. Monte Carlo simulations are used to show that the prompt quarantine measure outperforms random and acquaintance preventive vaccination schemes in terms of reducing the number of infected individuals. The epidemic threshold for the SIR model is analytically derived under the quarantine measure, and the theoretical findings indicate that prompt executions of quarantines are highly effective in containing epidemics. Even if infected individuals are detected with a very low probability, the SIR model under a prompt quarantine measure has finite epidemic thresholds in fat-tailed scale-free networks in which an infected individual can always cause an outbreak of a finite relative size without any measure. The numerical simulations also demonstrate that the present quarantine measure is effective in suppressing epidemics in real networks.

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“…Thus, social media might be a promising source of information in order to provide a better understanding of social dynamics within urban environments and resulted in various research efforts. Regarding the analysis of collective human mobility and activity patterns from social media, Cho et al (2011) investigate social ties and their influence on human mobility patterns by comparing social media check-in data and cellphone location data. They found a stronger association of social network ties influencing long-distance travel than short range spatially and temporally periodic movements.…”

Section: Utilization Of Social Media Data For Investigating Urban Envmentioning

confidence: 99%