Incorporating structural diversity of neighbors in a diffusion model for social networks

Qing Bao, Kwok Wai CHEUNG, Yu ZHANG

Research output: Chapter in book/report/conference proceedingConference proceedingpeer-review

7 Citations (Scopus)

Abstract

Diffusion is known to be an important process governing the behaviours observed in network environments like social networks, contact networks, etc. For modeling the diffusion process, the Independent Cascade Model (IC Model) is commonly adopted and algorithms have been proposed for recovering the hidden diffusion network based on observed cascades. However, the IC Model assumes the effects of multiple neighbors on a node to be independent and does not consider the structural diversity of nodes' neighbourhood. In this paper, we propose an extension of the IC Model with the community structure of node neighbours incorporated. We derive an expectation maximization (EM) algorithm to infer the model parameters. To evaluate the effectiveness and efficiency of the proposed method, we compared it with the IC model and its variants that do not consider the structural properties. Our empirical results based on the MemeTracker dataset, shows that after incorporating the structural diversity, there is a significant improvement in the modelling accuracy, with reasonable increase in run-time.

Original languageEnglish
Title of host publicationProceedings- 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)
PublisherIEEE Computer Society
Pages431-438
Number of pages8
ISBN (Print)9781479929023
DOIs
Publication statusPublished - 1 Jan 2013
Event2013 12th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013 - Atlanta, GA, United States
Duration: 17 Nov 201320 Nov 2013

Publication series

NameProceedings- 2013 IEEE/WIC/ACM International Joint Conferences on Web Intelligence (WI) and Intelligent Agent Technologies (IAT)
Volume1

Conference

Conference2013 12th IEEE/WIC/ACM International Conference on Web Intelligence, WI 2013
Country/TerritoryUnited States
CityAtlanta, GA
Period17/11/1320/11/13

Scopus Subject Areas

  • Artificial Intelligence

User-Defined Keywords

  • Diffusion network
  • Independent Cascade Model
  • Social networks
  • Structural diversity

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