Skip to main content

Modeling Link Formation Behaviors in Dynamic Social Networks

  • Conference paper
Social Computing, Behavioral-Cultural Modeling and Prediction (SBP 2011)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 6589))

Abstract

Online social networks are dynamic in nature. While links between users are seemingly formed and removed randomly, there exists some interested link formation behaviors demonstrated by users performing link creation and removal activities. Uncovering these behaviors not only allows us to gain deep insights of the users, but also pave the way to decipher how social links are formed. In this paper, we propose a general framework to define user link formation behaviors using well studied local link structures (i.e., triads and dyads) in a dynamic social network where links are formed at different timestamps. Depending on the role a user plays in a link structure, we derive different types of link formation behaviors. We develop models for these behaviors and measure them for a set of users in an Epinions dataset.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Faust, K.: Very local structure in social networks. Sociological Methodology 31(1), 209–256 (2007)

    Article  Google Scholar 

  2. Leskovec, J., Backstrom, L., Kumar, R., Tomkins, A.: Microscopic evolution of social networks. In: SIGKDD (2008)

    Google Scholar 

  3. Leskovec, J., Kleinberg, J., Faloutsos, C.: Graphs over time: densification laws, shrinking diameters and possible explanations. In: SIGKDD (2005)

    Google Scholar 

  4. Leung, C.W.-K., Lim, E.-P., Lo, D., Weng, J.: Mining interesting link formation rules in social networks. In: CIKM (2010)

    Google Scholar 

  5. Milo, R., Shen-Orr, S., Itzkovitz, S., Kashtan, N., Chklovskii, D., Alon, U.: Network motifs: Simple building blocks of complex networks. Science 298(5594), 824–827 (2002)

    Article  Google Scholar 

  6. Newman, M.E.J.: The structure and function of complex networks. SIAM Review 45, 167–256 (2003)

    Article  MATH  Google Scholar 

  7. Nguyen, V.-A., Lim, E.-P., Tan, H.-H., Jiang, J., Sun, A.: Do you trust to get trust? A study of trust reciprocity behaviors and reciprocal trust prediction. In: SIAM SDM (2010)

    Google Scholar 

  8. Romero, D.M., Kleinberg, J.: The directed closure process in hybrid social-information networks, with an analysis of link formation on Twitter. In: ICWSM (2010)

    Google Scholar 

  9. Snijders, T.A.B., Van de Bunt, G.G., Steglich, C.E.G.: Introduction to stochastic actor-based models for network dynamics. Social Networks, Special Issue on Dynamics of Social Networks 32(1), 44–60 (2010)

    Google Scholar 

  10. Wasserman, S., Faust, K.: Social Network Analysis: Methods and Applications. Cambridge University Press, Cambridge (1994)

    Book  MATH  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2011 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Nguyen, VA., Leung, C.WK., Lim, EP. (2011). Modeling Link Formation Behaviors in Dynamic Social Networks. In: Salerno, J., Yang, S.J., Nau, D., Chai, SK. (eds) Social Computing, Behavioral-Cultural Modeling and Prediction. SBP 2011. Lecture Notes in Computer Science, vol 6589. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-19656-0_48

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-19656-0_48

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-19655-3

  • Online ISBN: 978-3-642-19656-0

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics