Viral information propagation in the Digg online social network

Mark Freeman, James McVittie, Iryna Sivak and Jianhong Wu

Physica A: Statistical Mechanics and its Applications, 2014, vol. 415, issue C, 87-94

Abstract: We propose the use of a variant of the epidemiological SIR model to accurately describe the diffusion of online content over the online social network Digg.com. We examine the qualitative properties of our viral information propagation model, demonstrate the model’s applications to social media spread in online social networks with particular focus on accurately predicting user voting behavior over a period of 50 h. The model allows us to characterize the peak time, turning point, viral period and final size (total number of votes), and gives much improved prediction of user voting behaviors than other established models.

Keywords: Online social network; Digg network; Information spread; Mathematical epidemiology; Richards model (search for similar items in EconPapers)
Date: 2014
References: View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:phsmap:v:415:y:2014:i:c:p:87-94

DOI: 10.1016/j.physa.2014.06.011

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