Article

Analysis of topological characteristics of huge online social networking services

Authors:

Hawoong JeongAuthors Info & Claims

WWW '07: Proceedings of the 16th international conference on World Wide Web

Pages 835 - 844

https://doi.org/10.1145/1242572.1242685

Published: 08 May 2007 Publication History

Abstract

Social networking services are a fast-growing business in the Internet. However, it is unknown if online relationships and their growth patterns are the same as in real-life social networks. In this paper, we compare the structures of three online social networking services: Cyworld, MySpace, and orkut, each with more than 10 million users, respectively. We have access to complete data of Cyworld's ilchon (friend) relationships and analyze its degree distribution, clustering property, degree correlation, and evolution over time. We also use Cyworld data to evaluate the validity of snowball sampling method, which we use to crawl and obtain partial network topologies of MySpace and orkut. Cyworld, the oldest of the three, demonstrates a changing scaling behavior over time in degree distribution. The latest Cyworld data's degree distribution exhibits a multi-scaling behavior, while those of MySpace and orkut have simple scaling behaviors with different exponents. Very interestingly, each of the two e ponents corresponds to the different segments in Cyworld's degree distribution. Certain online social networking services encourage online activities that cannot be easily copied in real life; we show that they deviate from close-knit online social networks which show a similar degree correlation pattern to real-life social networks.

References

[1]

Techweb. http://www.techweb.com.

[2]

G. Kossinets. Effects of missing data in social networks. Preprint, arXiv.org:cond-mat/0306335, 2003.

[3]

A.-L. Barabasi and R. Albert. Emergence of scaling in random networks. Science, 286:509, 1999.

[4]

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

Digital Library

[5]

M. E. J. Newman. Scientific collaboration networks. I. network construction and fundamental results. Phys. Rev. E, 64:016131, July 2001.

[6]

F. Liljeros, C. R. Edling, L. A. N. Amaral, H. E. Stanley, and Y. Aberg. The web of human sexual contacts. Nature, 411:907, 2001.

[7]

A. Russo and J. Watkins. Digital cultural communication: Enabling new media and cocreation in southeast asia. International Journal of Education and Development using Information and Communication Technology, 1(4), 2005.

[8]

P. Holme, C. R. Edling, and F. Liljeros. Structure and time-evolution of an internet dating community. Social Networks, 26:155, 2004.

[9]

D. Liben-Nowell, J. Novak, R. Kumar, P. Raghavan, and A. Tomkins. Geographic Routing in social networks. Proceedings of the National Academy of Sciences, 102(33):11623--11628, Aug. 2005.

[10]

S. H. Lee, P. -J. Kim, and H. Jeong. Statistical properties of sampled networks. Phys. Rev. E, 73:016102, 2006.

[11]

R. Pastor-Satorras and A. Vespignani. Epidemic spreading in scale-free networks. Phys. Rev. Lett., 86:3200, 2001.

[12]

M. E. J. Newman. The spread of epidemic disease on networks. Phys. Rev. E, 66:016128, 2002.

[13]

R. Cohen and S. Havlin. Scale-free networks are ultrasmall. Phys. Rev. Lett., 90:058701, 2003.

[14]

R. Albert, H. Jeong, and A. -L. Barabasi. Error and attack tolerance of complex networks. Nature, 406:378, 2000.

[15]

M. E. J. Newman. Assortative mixing in networks. Phys. Rev. Lett., 89:208701, 2002.

[16]

M. E. J. Newman. Mixing patterns in networks. Phys. Rev. E, 67:026126, 2003.

[17]

M. E. J. Newman and J. Park. Why social networks are different from other types of networks. Phys. Rev. E, 68:036122, 2003.

[18]

S. Milgram. The small world problem. Psychology Today, 2:60--67, 1967.

[19]

M. E. J. Newman, S. H. Strogatz, and D. J. Watts. Random graphs with arbitrary degree distributions and their applications. Phys. Rev. E, 64:026118, 2001.

[20]

C. Palmer, P. Gibbons, and C. Faloutsos. ANF: A fast and scalable tool for data mining in massive graphs. In SIGKDD, 2002.

Digital Library

[21]

comscore. 694 million people currently use the internet worldwide according to comScore networks, 2006.

[22]

H. Kwak, S. Han, Y.-Y. Ahn, S. Moon, and H. Jeong. Impact of snowball sampling ratios on network characteristics estimation: A case study of Cyworld. Technical Report CS-TR-2006-262, KAIST, 2006.

[23]

J. Davidsen, H. Ebel, and S. Bornholdt. Emergence of a small world from local interactions: Modeling acquaintance networks. Physical Review Letters, 88:128701, 2002.

[24]

K. I. Goh, B. Kahng, and D. Kim. Universal behavior of load distribution in scale-free networks. Physical Review Letters, 87:278701, 2001.

[25]

G. Bianconi and A. L. Barabasi. Competition and multiscaling in evolving networks. Europhys. Lett., 54:436, 2001.

[26]

G. Caldarelli, A. Capocci, P. De Los Rios, and M. A. Munoz. Scale-free networks from varying vertex intrinsic fitness. Phys. Rev. Lett., 89(25), December 2002.

[27]

R. I. M. Dunbar. Coevolution of neocortical size, group size and language in humans. Behavioral and Brain Sciences, 16(4):681--735, 1993. WWW 2007 / Track: Semantic Web Session: Semantic Web and Web 2.0

Cited By

Esmaili MChristensen K(2025)Performance Modeling of Public Permissionless Blockchains: A SurveyACM Computing Surveys10.1145/371509457:7(1-35)Online publication date: 20-Feb-2025
https://dl.acm.org/doi/10.1145/3715094
He XGhasemian ALee ESchwarze AClauset AMucha P(2024)Link prediction accuracy on real-world networks under non-uniform missing-edge patternsPLOS ONE10.1371/journal.pone.030688319:7(e0306883)Online publication date: 18-Jul-2024
https://doi.org/10.1371/journal.pone.0306883
P TG K(2024)Systematic review on utilization of WhatsApp in educationE-Learning and Digital Media10.1177/20427530241239424Online publication date: 21-Mar-2024
https://doi.org/10.1177/20427530241239424
Show More Cited By

Index Terms

Analysis of topological characteristics of huge online social networking services
1. Applied computing
  1. Law, social and behavioral sciences
    1. Sociology

Recommendations

Effects of System Characteristics on Users' Self-Disclosure in Social Networking Sites
ITNG '10: Proceedings of the 2010 Seventh International Conference on Information Technology: New Generations

Social networking sites (SNSs) (e.g., Facebook) are increasingly used in people’s daily life and business worlds. With SNSs, people’s social networks are expanded by connecting to others with shared interests or values based on other users’ self-...
Investigating Homophily in Online Social Networks
WI-IAT '10: Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 01

Similarity breeds connections, the principle of homophily, has been well studied in existing sociology literature. %Several studies have observed this phenomena by conducting surveys on human subjects. These studies have concluded that new ties are ...
Online Bonding and Bridging Social Capital via Social Networking Sites

This research aimed to explore types of online social capital bridging and bonding that the Emiratis perceive in the context of social networking site SNS usage. A snow-ball sample of 230 Emiratis from two Emirates, Abu Dhabi and Dubai was used. The ...

Comments

Information & Contributors

Information

Published In

cover image ACM Conferences

WWW '07: Proceedings of the 16th international conference on World Wide Web

May 2007

1382 pages

ISBN:9781595936547

DOI:10.1145/1242572

General Chairs:
Carey Williamson
University of Calgary, Canada
,
Mary Ellen Zurko
IBM, USA
,
Program Chairs:
Peter Patel-Schneider
Bell Labs Research, USA
,
Prashant Shenoy
University of Massachusetts at Amherst, USA

Copyright © 2007 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Sponsors

ACM: Association for Computing Machinery

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 May 2007

Permissions

Request permissions for this article.

Request Permissions

Check for updates

Author Tags

Qualifiers

Article

Conference

WWW'07

Sponsor:

ACM

WWW'07: 16th International World Wide Web Conference

May 8 - 12, 2007

Alberta, Banff, Canada

Acceptance Rates

Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

607
Total Citations
View Citations
8,372
Total Downloads

Downloads (Last 12 months)141
Downloads (Last 6 weeks)11

Reflects downloads up to 18 Feb 2025

Other Metrics

View Author Metrics

Citations

Cited By

Esmaili MChristensen K(2025)Performance Modeling of Public Permissionless Blockchains: A SurveyACM Computing Surveys10.1145/371509457:7(1-35)Online publication date: 20-Feb-2025
https://dl.acm.org/doi/10.1145/3715094
He XGhasemian ALee ESchwarze AClauset AMucha P(2024)Link prediction accuracy on real-world networks under non-uniform missing-edge patternsPLOS ONE10.1371/journal.pone.030688319:7(e0306883)Online publication date: 18-Jul-2024
https://doi.org/10.1371/journal.pone.0306883
P TG K(2024)Systematic review on utilization of WhatsApp in educationE-Learning and Digital Media10.1177/20427530241239424Online publication date: 21-Mar-2024
https://doi.org/10.1177/20427530241239424
Zhang ZZhao JWang GJohnston SChalhoub GRoss TLiu DTinsman CZhao RVan Kleek MShadbolt N(2024)Trouble in Paradise? Understanding Mastodon Admin's Motivations, Experiences, and Challenges Running Decentralised Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/36870598:CSCW2(1-24)Online publication date: 8-Nov-2024
https://dl.acm.org/doi/10.1145/3687059
Gassmann LMcConville REdwards M(2024)Leading the Mastodon Herd: Analysing the Traits of Influential Leaders on a Decentralised Social Media Platform2024 IEEE International Conference on Big Data (BigData)10.1109/BigData62323.2024.10825842(2939-2948)Online publication date: 15-Dec-2024
https://doi.org/10.1109/BigData62323.2024.10825842
Nian 年 FYao 姚 R(2024)A Weibo local network growth model constructed from the perspective of following–followedChinese Physics B10.1088/1674-1056/ad84c433:12(128702)Online publication date: 1-Dec-2024
https://doi.org/10.1088/1674-1056/ad84c4
Wang JZhang YXu CLi JSun JXie JFeng LZhou THu Y(2024)Reconstructing the evolution history of networked complex systemsNature Communications10.1038/s41467-024-47248-x15:1Online publication date: 2-Apr-2024
https://doi.org/10.1038/s41467-024-47248-x
Jahan NHoque SHossain MHoon JPipul M(2024)SNS Citizenship Behavior Based on D&M Information System Success Model and Social Capital Theory: Mediating Role of Subjective Well-beingHeliyon10.1016/j.heliyon.2024.e29982(e29982)Online publication date: Apr-2024
https://doi.org/10.1016/j.heliyon.2024.e29982
Hasegawa THironaka SShudo K(2024)Estimation of Graph Features Based on Random Walks Using Neighbors’ PropertiesWeb Information Systems Engineering – WISE 202410.1007/978-981-96-0567-5_32(456-466)Online publication date: 3-Dec-2024
https://doi.org/10.1007/978-981-96-0567-5_32
Zuo WRaman AMondragÓN RTyson G(2023)A First Look at User-Controlled Moderation on Web3 Social Media: The Case of Memo.cashProceedings of the 3rd International Workshop on Open Challenges in Online Social Networks10.1145/3599696.3612901(29-37)Online publication date: 4-Sep-2023
https://dl.acm.org/doi/10.1145/3599696.3612901
Show More Cited By

View Options

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

View options

PDF

View or Download as a PDF file.

eReader

View online with eReader.

Figures

Tables

Media

View Table of Conten