Ensuring Relevant and Serendipitous Information Flow in Decentralized Online Social Network

  • Udeep Tandukar
  • Julita Vassileva
Conference paper

DOI: 10.1007/978-3-642-33185-5_9

Volume 7557 of the book series Lecture Notes in Computer Science (LNCS)
Cite this paper as:
Tandukar U., Vassileva J. (2012) Ensuring Relevant and Serendipitous Information Flow in Decentralized Online Social Network. In: Ramsay A., Agre G. (eds) Artificial Intelligence: Methodology, Systems, and Applications. AIMSA 2012. Lecture Notes in Computer Science, vol 7557. Springer, Berlin, Heidelberg

Abstract

This paper presents a novel peer-to-peer architecture for decentralized Online Social Network and a mechanism that allows each node to filter out irrelevant social data, while ensuring a level of serendipity, by letting important information pass, even if it does not fall in the areas of interest of the user. The evaluation of the approach, using an Erlang simulation with 2318 nodes shows that it works as it was designed to: with the increasing number of social data passing through the network, the nodes learn to filter out irrelevant data, while serendipitous important data is able to pass through the network. Future work will implement the mechanism in a decentralized OSN and evaluate it in a real community of users, in an enterprise context.

Keywords

Information propagation Online Social Network Decentralization Peer-to-peer system Relationship modeling 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Udeep Tandukar
    • 1
  • Julita Vassileva
    • 1
  1. 1.Department of Computer ScienceUniversity of SaskatchewanSaskatchewanCanada