Peer and Authority Pressure in Information-Propagation Models

  • Aris Anagnostopoulos
  • George Brova
  • Evimaria Terzi
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6911)


Existing models of information diffusion assume that peer influence is the main reason for the observed propagation patterns. In this paper, we examine the role of authority pressure on the observed information cascades. We model this intuition by characterizing some nodes in the network as “authority” nodes. These are nodes that can influence large number of peers, while themselves cannot be influenced by peers. We propose a model that associates with every item two parameters that quantify the impact of the peer and the authority pressure on the item’s propagation. Given a network and the observed diffusion patterns of the item, we learn these parameters from the data and characterize the item as peer- or authority-propagated. We also develop a randomization test that evaluates the statistical significance of our findings and makes our item characterization robust to noise. Our experiments with real data from online media and scientific-collaboration networks indicate that there is a strong signal of authority pressure in these networks.


Randomization Test Collaboration Network Information Item Online Medium News Site 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Aris Anagnostopoulos
    • 1
  • George Brova
    • 2
  • Evimaria Terzi
    • 2
  1. 1.Department of Computer and System SciencesSapienza University of RomeItaly
  2. 2.Computer Science DepartmentBoston UniversityUSA

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