Characterizing information diffusion in online social networks with linear diffusive model

Feng Wang, Haiyan Wang, Kuai Xu, Jianhong Wu, Xiaohua Jia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

49 Scopus citations

Abstract

Mathematical modeling is an important approach to study information diffusion in online social networks. Prior studies have focused on the modeling of the temporal aspect of information diffusion. A recent effort introduced the spatiotemporal diffusion problem and addressed the problem with a theoretical framework built on the similarity between information propagation in online social networks and biological invasion in ecology [1]. This paper examines the spatio-temporal characteristics in further depth and reveals that there exist regularities in information diffusion in temporal and spatial dimensions. Furthermore, we propose a simpler linear partial differential equation that takes account of the influence of spatial population density and temporal decay of user interests in the information. We validate the proposed linear model with Digg news stories which received more than 3000 votes during June 2009, and show that the model can describe nearly 60% of the news stories with over 80% accuracy. We also use the most popular news story as a case study and find that the linear diffusive model can achieve an accuracy as high as 97:41% for this news story. Finally, we discuss the potential applications of this model towards finding super spreaders and classifying news story into groups.

Original languageEnglish (US)
Title of host publicationProceedings - 2013 IEEE 33rd International Conference on Distributed Computing Systems, ICDCS 2013
Pages307-316
Number of pages10
DOIs
StatePublished - Dec 1 2013
Event2013 IEEE 33rd International Conference on Distributed Computing Systems, ICDCS 2013 - Philadelphia, PA, United States
Duration: Jul 8 2013Jul 11 2013

Publication series

NameProceedings - International Conference on Distributed Computing Systems

Other

Other2013 IEEE 33rd International Conference on Distributed Computing Systems, ICDCS 2013
CountryUnited States
CityPhiladelphia, PA
Period7/8/137/11/13

Keywords

  • PDE
  • information diffusion
  • mathematical modeling
  • online social network
  • spatio-temporal

ASJC Scopus subject areas

  • Software
  • Hardware and Architecture
  • Computer Networks and Communications

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    Wang, F., Wang, H., Xu, K., Wu, J., & Jia, X. (2013). Characterizing information diffusion in online social networks with linear diffusive model. In Proceedings - 2013 IEEE 33rd International Conference on Distributed Computing Systems, ICDCS 2013 (pp. 307-316). [6681600] (Proceedings - International Conference on Distributed Computing Systems). https://doi.org/10.1109/ICDCS.2013.14