Skip to main content
SpringerLink
Log in

Agent Perspective Social Networks: Distributed Second Degree Estimation

  • Living reference work entry
  • First Online:
Encyclopedia of Social Network Analysis and Mining

Synonyms

Friends of friends; Two-hop neighbors

Glossary

Observations:

Observed activities or interactions between users in a social system

Degree Distributions:

Probability distribution of degrees of users in a social system

Definition

Second neighbors of a node are two-hop reachable nodes. Second degree of a node is the sum of degrees of second neighbors.

Introduction

In general, social network analysis algorithms are concerned about understanding overall properties of networks. The observer, in these cases, studies a given network from an objective perspective. On the other hand, a node-centric analysis is for each node within the network to reason about the network it belongs to. The focus of this research interest is to design algorithms for each node to use to reason about its own world. The difficulties in obtaining an accurate and complete social network structure make a node-centric approach extremely attractive. Furthermore, as the number of devices connected to people...

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

Access this chapter

Log in via an institution

Institutional subscriptions

References

  • Albert R, Barabási AL (2002) Statistical mechanics of complex networks. Rev Mod Phys 74(1):47–97. doi:10.1103/RevModPhys.74.47

    Article  MathSciNet  MATH  Google Scholar 

  • Casella G, Berger R (2001) Statistical inference. Duxbury Resource Center, Pacific Grove

    Google Scholar 

  • Clauset A, Shalizi CR, Newman MEJ (2009) Power-law distributions in empirical data. SIAM Rev 51(4):661–703. doi:10.1137/070710111

    Article  MathSciNet  MATH  Google Scholar 

  • Csanyi G, Szendroi B (2004) Structure of a large social network. Phys Rev E 69(3):036,131, pT: J; PN: Part 2; PG: 5

    Google Scholar 

  • ErdÅ‘s P, Rényi A (1959) On random graphs, I. Publicationes Mathematicae (Debrecen) 6:290–297, URL: http://www.renyi.hu/Ëœ{}p_erdos/Erdos.html#1959-11

  • Galeotti A, Goyal S, Jackson MO, Vega-Redondo F, Yariv L (2010) Network games. Rev Eco Stud 77(1):218–244

    Article  MathSciNet  MATH  Google Scholar 

  • Gillespie CS (2014) Fitting heavy tailed distributions: the poweRlaw package. R package version 0.20.5, arXiv preprint arXiv:1407.3492 (2014). https://www.jstatsoft.org/article/view/v064i02

  • Hay M, Li C, Miklau G, Jensen D (2009) Accurate estimation of the degree distribution of private networks. In: Proceedings of the 2009 Ninth IEEE International Conference on Data Mining, IEEE Computer Society. ICDM ‘09, Washington, DC, pp 169–178. doi:10.1109/ICDM. 2009.11

    Chapter  Google Scholar 

  • Kupavskii A, Ostroumova L, Shabanov DA, Tetali P (2013) The distribution of second degrees in the buckley-osthus random graph model. Internet Math 9(4):297–335. URL: http://dblp.uni-trier.de/db/journals/im/im9.html#KupavskiiOST13

  • Lee JY, Oh JC (2013) A model for recursive propagations of reputations in social networks. In: Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, ACM. ASONAM ’13, New York, pp 666–670. doi:10.1145/ 2492517.2492663

    Google Scholar 

  • Lenzen C, Wattenhofer R (2012) Distributed Algorithms for Sensor Networks. Philos Trans Royal Soc A 370(1958)

    Google Scholar 

  • Mislove A, Marcon M, Gummadi KP, Druschel P, Bhattacharjee B (2007a) Measurement and analysis of online social networks. In: Proceedings of the 7th ACM SIGCOMM Conference on Internet Measurement, ACM. IMC ’07, New York, pp 29–42. doi:10.1145/1298306. 1298311

    Chapter  Google Scholar 

  • Mislove A, Marcon M, Gummadi KP, Druschel P, Bhattacharjee B (2007b) Measurement and analysis of online social networks. In: Proceedings of the 5th ACM/USENIX Internet Measurement Conference (IMC’07), San Diego, 24–26 October 2007

    Google Scholar 

  • Newman MEJ, Girvan M (2004) Finding and evaluating community structure in networks. Phys Rev E 69(2):026,113. doi:10.1103/PhysRevE.69.026113

    Article  Google Scholar 

  • Page L, Brin S, Motwani R, Winograd T (1999) The pagerank citation ranking: Bringing order to the web. Technical Report 1999–66, Stanford InfoLab. URL: http://ilpubs.stanford.edu:8090/422/

  • Ribeiro BF, Towsley D (2012a) On the estimation accuracy of degree distributions from graph sampling. In: CDC, pp 5240–5247

    Google Scholar 

  • Ribeiro BF, Towsley D (2012b) On the estimation accuracy of degree distributions from graph sampling. In: CDC, pp 5240–5247

    Google Scholar 

  • Shannon P, Markiel A, Ozier O, Baliga NS, Wang JT, Ramage D, Amin N, Schwikowski B, Ideker T (2003) Cytoscape: a software environment for integrated models of biomolecular interaction networks. Genome Res 13(11):2498–2504. doi:10.1101/gr.1239303

    Article  Google Scholar 

  • Snijders TAB (2003) Accounting for degree distributions in empirical analysis of network dynamics. In: Proceedings of the National Academy of Sciences USA, Academic Press, pp 109–114

    Google Scholar 

  • Viswanath B, Mislove A, Cha M, Gummadi KP (2009) On the evolution of user interaction in facebook. In: Proceedings of the 2nd ACM SIGCOMM Workshop on Social Networks (WOSN’09)

    Google Scholar 

  • Wang T, Chen Y, Zhang Z, Xu T, Jin L, Hui P, Deng B, Li X (2011) Understanding graph sampling algorithms for social network analysis. In: ICDCS Workshops, IEEE Computer Society, pp 123–128. URL: http://dblp.uni-trier.de/db/conf/icdcsw/icdcsw2011.html#WangCZXJHDL11

  • Ye S, Wu SF (2010) Estimating the size of online social networks. In: Elmagarmid AK, Agrawal D (eds) SocialCom/PASSAT, IEEE Computer Society, pp 169–176. URL: http://dblp.uni-trier.de/db/conf/socialcom/socialcom2010.html#YeW10

Download references

Author information

Authors and Affiliations

  1. Department of Computer Science, Innopolis University, Innopolis, Russia

    Joo Young Lee

  2. Department of Electrical Engineering and Computer Science, Syracuse University, Syracuse, NY, 13214, USA

    Jae C. Oh

Authors
  1. Joo Young Lee
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Jae C. Oh
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Joo Young Lee .

Editor information

Editors and Affiliations

  1. Computer Science, University of Calgary, Calgary, Alberta, Canada

    Reda Alhajj

  2. University of Calgary Computer Science, Calgary, Canada

    Jon Rokne

Section Editor information

  1. Department of Computer Science and Management, Institute of Informatics, Wrocław University of Technology, Wrocław, Poland

    Przemysław Kazienko

  2. Faculty of Computer Science and Information Technology, West Pomeranian University of Technology, Szczecin, Poland

    Jaroslaw Jankowski

Rights and permissions

Reprints and permissions

Copyright information

© 2016 Springer Science+Business Media LLC

About this entry

Cite this entry

Lee, J.Y., Oh, J.C. (2016). Agent Perspective Social Networks: Distributed Second Degree Estimation. In: Alhajj, R., Rokne, J. (eds) Encyclopedia of Social Network Analysis and Mining. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-7163-9_110187-1

Download citation

  • DOI: https://doi.org/10.1007/978-1-4614-7163-9_110187-1

  • Received:

  • Accepted:

  • Published:

  • Publisher Name: Springer, New York, NY

  • Print ISBN: 978-1-4614-7163-9

  • Online ISBN: 978-1-4614-7163-9

  • eBook Packages: Springer Reference Computer SciencesReference Module Computer Science and Engineering

Publish with us

Policies and ethics

Search

Navigation