Skip to main content
SpringerLink
Log in

Finding Diverse Friends in Social Networks

  • Conference paper
Web Technologies and Applications (APWeb 2013)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 7808))

Included in the following conference series:

Abstract

Social networks are usually made of users linked by friendship, which can be dependent on (or influenced by) user characteristics (e.g., connectivity, centrality, weight, importance, activity in the networks). Among many friends of these social network users, some friends are more diverse (e.g., more influential, prominent, and/or active in a wide range of domains) than other friends in the networks. Recognizing these diverse friends can provide valuable information for various real-life applications when analyzing and mining huge volumes of social network data. In this paper, we propose a tree-based mining algorithm that finds diverse friends, who are highly influential across multiple domains, in social networks.

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

Access this chapter

Log in via an institution
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. Agrawal, R., Srikant, R.: Fast algorithms for mining association rules in large databases. In: VLDB 1994, pp. 487–499 (1994)

    Google Scholar 

  2. Anagnostopoulos, A., Kumar, R., Mahdian, M.: Influence and correlation in social networks. In: ACM KDD 2008, pp. 7–15 (2008)

    Google Scholar 

  3. Cameron, J.J., Leung, C.K.-S., Tanbeer, S.K.: Finding strong groups of friends among friends in social networks. In: IEEE DASC/SCA 2011, pp. 824–831 (2011)

    Google Scholar 

  4. Han, J., Pei, J., Yin, Y.: Mining frequent patterns without candidate generation. In: ACM SIGMOD 2000, pp. 1–12 (2000)

    Google Scholar 

  5. Jiang, F., Leung, C.K.-S., Tanbeer, S.K.: Finding popular friends in social networks. In: CGC/SCA 2012, pp. 501–508. IEEE (2012)

    Google Scholar 

  6. Kamath, K.Y., Caverlee, J., Cheng, Z., Sui, D.Z.: Spatial influence vs. community influence: modeling the global spread of social media. In: ACM CIKM 2012, pp. 962–971 (2012)

    Google Scholar 

  7. Lee, W., Leung, C.K.-S., Song, J.J., Eom, C.S.-H.: A network-flow based influence propagation model for social networks. In: CGC/SCA 2012, pp. 601–608. IEEE (2012)

    Google Scholar 

  8. Lee, W., Song, J.J., Leung, C.K.-S.: Categorical data skyline using classification tree. In: Du, X., Fan, W., Wang, J., Peng, Z., Sharaf, M.A. (eds.) APWeb 2011. LNCS, vol. 6612, pp. 181–187. Springer, Heidelberg (2011)

    Chapter  Google Scholar 

  9. Leung, C.K.-S., Carmichael, C.L.: Exploring social networks: a frequent pattern visualization approach. In: IEEE SocialCom 2010, pp. 419–424 (2010)

    Google Scholar 

  10. Leung, C.K.-S., Tanbeer, S.K.: Mining social networks for significant friend groups. In: Yu, H., Yu, G., Hsu, W., Moon, Y.-S., Unland, R., Yoo, J. (eds.) DASFAA Workshops 2012. LNCS, vol. 7240, pp. 180–192. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  11. Peng, Z., Wang, C., Han, L., Hao, J., Ou, X.: Discovering the most potential stars in social networks with infra-skyline queries. In: Sheng, Q.Z., Wang, G., Jensen, C.S., Xu, G. (eds.) APWeb 2012. LNCS, vol. 7235, pp. 134–145. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  12. Sachan, M., Contractor, D., Faruquie, T.A., Subramaniam, L.V.: Using content and interactions for discovering communities in social networks. In: ACM WWW 2012, pp. 331–340 (2012)

    Google Scholar 

  13. Schaal, M., O’Donovan, J., Smyth, B.: An analysis of topical proximity in the twitter social graph. In: Aberer, K., Flache, A., Jager, W., Liu, L., Tang, J., Guéret, C. (eds.) SocInfo 2012. LNCS, vol. 7710, pp. 232–245. Springer, Heidelberg (2012)

    Chapter  Google Scholar 

  14. Sun, Y., Barber, R., Gupta, M., Aggarwal, C.C., Han, J.: Co-author relationship prediction in heterogeneous bibliographic networks. In: ASONAM 2011, pp. 121–128. IEEE (2011)

    Google Scholar 

  15. Tanbeer, S.K., Leung, C.K.-S., Cameron, J.J.: DIFSoN: discovering influential friends from social networks. In: CASoN 2012, pp. 120–125. IEEE (2012)

    Google Scholar 

  16. Yang, X., Ghoting, A., Ruan, Y., Parthasarathy, S.: A framework for summarizing and analyzing twitter feeds. In: ACM KDD 2012, pp. 370–378 (2012)

    Google Scholar 

  17. Zhang, C., Shou, L., Chen, K., Chen, G., Bei, Y.: Evaluating geo-social influence in location-based social networks. In: ACM CIKM 2012, pp. 1442–1451 (2012)

    Google Scholar 

  18. Zhang, S., Zhang, C., Yan, X.: Post-mining: maintenance of association rules by weighting. Information Systems 28(7), 691–707 (2003)

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, University of Manitoba, Canada

    Syed Khairuzzaman Tanbeer & Carson Kai-Sang Leung

Authors
  1. Syed Khairuzzaman Tanbeer
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Carson Kai-Sang Leung
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Department of Information Engineering, Nagoya University, 464-8601, Nagoya, Japan

    Yoshiharu Ishikawa

  2. Department of Computer Science and Technology, Harbin Institute of Technology, 150006, Harbin, China

    Jianzhong Li

  3. School of Computer Science and Engineering, University of New South Wales, 2031, Sydney, NSW, Australia

    Wei Wang  & Wenjie Zhang  & 

  4. Department of Computing and Information Systems, University of Melbourne, 3052, Melbourne, VIC, Australia

    Rui Zhang

Rights and permissions

Reprints and permissions

Copyright information

© 2013 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

Tanbeer, S.K., Leung, C.KS. (2013). Finding Diverse Friends in Social Networks. In: Ishikawa, Y., Li, J., Wang, W., Zhang, R., Zhang, W. (eds) Web Technologies and Applications. APWeb 2013. Lecture Notes in Computer Science, vol 7808. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-37401-2_31

Download citation

  • DOI: https://doi.org/10.1007/978-3-642-37401-2_31

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-37400-5

  • Online ISBN: 978-3-642-37401-2

  • eBook Packages: Computer ScienceComputer Science (R0)

Publish with us

Policies and ethics

Search

Navigation