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Contact prediction, routing and fast information spreading in social networks

The astronomical increase in the number of wireless devices such as smart phones in 21th century has revolutionized the way people communicate with one another and share information. The new wireless technologies have also enabled researchers to collect real data about how people move and meet one another in different social settings. Understanding human mobility has many applications in different areas such as traffic planning in cities and public health studies of epidemic diseases. In this thesis, we study the fundamental properties of human contact graphs in order to characterize how people meet one another in different social environments. Understanding human contact patterns in return allows us to propose a cost-effective routing algorithm for spreading information in Delay Tolerant Networks. Furthermore, we propose several contact predictors to predict the unobserved parts of contact graphs when only partial observations are available. Our results show that we are able to infer hidden contacts of real contact traces by exploiting the underlying properties of contact graphs.

In the last few years, we have also witnessed an explosion in the number of people who use social media to share information with their friends. In the last part of this thesis, we study the running times of several information spreading algorithms in social networks in order to find the fastest strategy. Fast information spreading has an obvious application in advertising a product to a large number of people in a short amount of time. We prove that a fast information spreading algorithm should efficiently identify communication bottlenecks in order to speed up the running time. Finally, we show that sparsifying large social graphs by exploiting the edge-betweenness centrality measure can also speed up the information spreading rate. / Graduate

  1. http://hdl.handle.net/1828/4139
  2. Jahanbakhsh, Kazem and Shoja, Gholamali C. and King, Valerie. Social-Greedy: a socially-based greedy routing algorithm for delay tolerant networks. MobiOpp '10: Proceedings of the Second International Workshop on Mobile Opportunistic Networking, 2010, pages = 159--162. Pisa, Italy, ACM {New York, NY, USA}.
  3. Jahanbakhsh, Kazem and Shoja, Gholamali C. and King, Valerie. International Symposium on Social Computing and Networking. Hangzhou, China. December, IEEE, Human Contact Prediction Using Contact Graph Inference, 2010, pages 813-818.
  4. Jahanbakhsh, Kazem and Shoja, Gholamali C. and King, Valerie. World of Wireless Mobile and Multimedia Networks. Lucca, Italy. June. IEEE. Predicting Missing Contacts in Mobile Social Networks, 2011.
  5. Jahanbakhsh, Kazem and King, Valerie and Shoja, Gholamali C. Predicting human contacts in mobile social networks using supervised learning. Proceedings of the Fourth Annual Workshop on Simplifying Complex Networks for Practitioners. SIMPLEX '12, 2012. Lyon, France, pages 37--42. ACM, New York, NY, USA.
  6. Kazem Jahanbakhsh and Valerie King and Gholamali C. Shoja. Empirical Comparison of Information Spreading Algorithms in the Presence of 1-Whiskers. SocialCom/PASSAT, 2011, pages 489-492.
  7. Predicting missing contacts in mobile social networks. "Pervasive and Mobile Computing", 2012, url http://www.sciencedirect.com/science/article/pii/S1574119212000910, Kazem Jahanbakhsh and Valerie King and Gholamali C. Shoja.
Identiferoai:union.ndltd.org:uvic.ca/oai:dspace.library.uvic.ca:1828/4139
Date20 August 2012
CreatorsJahanbakhsh, Kazem
ContributorsKing, Valerie D., Shoja, Gholamali C.
Source SetsUniversity of Victoria
LanguageEnglish, English
Detected LanguageEnglish
TypeThesis
RightsAvailable to the World Wide Web

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