Comparison of online social relations in terms of volume vs. interaction: A case study of cyworld

Hyunwoo Chun, Yong Yeol Ahn, Haewoon Kwak, Sue Moon, Young Ho Eom, Hawoong Jeong

Research output: Chapter in Book/Report/Conference proceedingConference contribution

92 Citations (Scopus)

Abstract

Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction. Does the interaction between users follow the declaration of friend relationship? Does a user interact evenly or lopsidedly with, friends? We venture to answer these questions in this work. We construct a network from comments written in guestbooks. A node represents a user and a directed, edge a comments from a user to another. We call this network an activity network. Previous work on activity networks include phone-call networks [34, 35] and MSN messenger networks [27]. To our best knowledge, this is the first attempt to compare the explicit friend relationship network and implicit activity network. We have analyzed structural characteristics of the activity network and compared them with the friends network. Though the activity network is weighted and directed, its structure is similar to the friend relationship network. We report that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated. When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks. The k-core analysis gives yet another corroborating evidence that the friends network deviates from the known social network and has an unusually large number of highly connected cores. We have delved into the weighted and directed nature of the activity network, and investigated the reciprocity, disparity, and network motifs. We also have observed that peer pressure to stay active online stops building up beyond a certain number of friends. The activity network has shown topological characteristics similar to the friends network, but thanks to its directed and weighted nature, it has allowed us more in-depth analysis of user interaction.

Original languageEnglish
Title of host publicationProceedings of the ACM SIGCOMM Internet Measurement Conference, IMC
Pages57-69
Number of pages13
DOIs
Publication statusPublished - 1 Dec 2008
Externally publishedYes
EventInternet Measurement Conference 2008, IMC'08 - Vouliagmeni, Greece
Duration: 20 Oct 200822 Oct 2008

Other

OtherInternet Measurement Conference 2008, IMC'08
CountryGreece
CityVouliagmeni
Period20/10/0822/10/08

Fingerprint

Internet
Core analysis
Recommender systems
Web services

Keywords

  • Clustering coefficient
  • Cyworld
  • Degree correlation
  • Degree distribution
  • Disparity
  • Friend relationship
  • Guestbook log
  • K-core
  • Network motif
  • Online social network
  • Reciprocity

ASJC Scopus subject areas

  • Software
  • Computer Networks and Communications

Cite this

Chun, H., Ahn, Y. Y., Kwak, H., Moon, S., Eom, Y. H., & Jeong, H. (2008). Comparison of online social relations in terms of volume vs. interaction: A case study of cyworld. In Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC (pp. 57-69) https://doi.org/10.1145/1452520.1452528

Comparison of online social relations in terms of volume vs. interaction : A case study of cyworld. / Chun, Hyunwoo; Ahn, Yong Yeol; Kwak, Haewoon; Moon, Sue; Eom, Young Ho; Jeong, Hawoong.

Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC. 2008. p. 57-69.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Chun, H, Ahn, YY, Kwak, H, Moon, S, Eom, YH & Jeong, H 2008, Comparison of online social relations in terms of volume vs. interaction: A case study of cyworld. in Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC. pp. 57-69, Internet Measurement Conference 2008, IMC'08, Vouliagmeni, Greece, 20/10/08. https://doi.org/10.1145/1452520.1452528
Chun H, Ahn YY, Kwak H, Moon S, Eom YH, Jeong H. Comparison of online social relations in terms of volume vs. interaction: A case study of cyworld. In Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC. 2008. p. 57-69 https://doi.org/10.1145/1452520.1452528
Chun, Hyunwoo ; Ahn, Yong Yeol ; Kwak, Haewoon ; Moon, Sue ; Eom, Young Ho ; Jeong, Hawoong. / Comparison of online social relations in terms of volume vs. interaction : A case study of cyworld. Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC. 2008. pp. 57-69
@inproceedings{a4e0149652bb4846a0a7f1ce7bf9969e,
title = "Comparison of online social relations in terms of volume vs. interaction: A case study of cyworld",
abstract = "Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction. Does the interaction between users follow the declaration of friend relationship? Does a user interact evenly or lopsidedly with, friends? We venture to answer these questions in this work. We construct a network from comments written in guestbooks. A node represents a user and a directed, edge a comments from a user to another. We call this network an activity network. Previous work on activity networks include phone-call networks [34, 35] and MSN messenger networks [27]. To our best knowledge, this is the first attempt to compare the explicit friend relationship network and implicit activity network. We have analyzed structural characteristics of the activity network and compared them with the friends network. Though the activity network is weighted and directed, its structure is similar to the friend relationship network. We report that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated. When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks. The k-core analysis gives yet another corroborating evidence that the friends network deviates from the known social network and has an unusually large number of highly connected cores. We have delved into the weighted and directed nature of the activity network, and investigated the reciprocity, disparity, and network motifs. We also have observed that peer pressure to stay active online stops building up beyond a certain number of friends. The activity network has shown topological characteristics similar to the friends network, but thanks to its directed and weighted nature, it has allowed us more in-depth analysis of user interaction.",
keywords = "Clustering coefficient, Cyworld, Degree correlation, Degree distribution, Disparity, Friend relationship, Guestbook log, K-core, Network motif, Online social network, Reciprocity",
author = "Hyunwoo Chun and Ahn, {Yong Yeol} and Haewoon Kwak and Sue Moon and Eom, {Young Ho} and Hawoong Jeong",
year = "2008",
month = "12",
day = "1",
doi = "10.1145/1452520.1452528",
language = "English",
isbn = "9781605583341",
pages = "57--69",
booktitle = "Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC",

}

TY - GEN

T1 - Comparison of online social relations in terms of volume vs. interaction

T2 - A case study of cyworld

AU - Chun, Hyunwoo

AU - Ahn, Yong Yeol

AU - Kwak, Haewoon

AU - Moon, Sue

AU - Eom, Young Ho

AU - Jeong, Hawoong

PY - 2008/12/1

Y1 - 2008/12/1

N2 - Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction. Does the interaction between users follow the declaration of friend relationship? Does a user interact evenly or lopsidedly with, friends? We venture to answer these questions in this work. We construct a network from comments written in guestbooks. A node represents a user and a directed, edge a comments from a user to another. We call this network an activity network. Previous work on activity networks include phone-call networks [34, 35] and MSN messenger networks [27]. To our best knowledge, this is the first attempt to compare the explicit friend relationship network and implicit activity network. We have analyzed structural characteristics of the activity network and compared them with the friends network. Though the activity network is weighted and directed, its structure is similar to the friend relationship network. We report that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated. When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks. The k-core analysis gives yet another corroborating evidence that the friends network deviates from the known social network and has an unusually large number of highly connected cores. We have delved into the weighted and directed nature of the activity network, and investigated the reciprocity, disparity, and network motifs. We also have observed that peer pressure to stay active online stops building up beyond a certain number of friends. The activity network has shown topological characteristics similar to the friends network, but thanks to its directed and weighted nature, it has allowed us more in-depth analysis of user interaction.

AB - Online social networking services are among the most popular Internet services according to Alexa.com and have become a key feature in many Internet services. Users interact through various features of online social networking services: making friend relationships, sharing their photos, and writing comments. These friend relationships are expected to become a key to many other features in web services, such as recommendation engines, security measures, online search, and personalization issues. However, we have very limited knowledge on how much interaction actually takes place over friend relationships declared online. A friend relationship only marks the beginning of online interaction. Does the interaction between users follow the declaration of friend relationship? Does a user interact evenly or lopsidedly with, friends? We venture to answer these questions in this work. We construct a network from comments written in guestbooks. A node represents a user and a directed, edge a comments from a user to another. We call this network an activity network. Previous work on activity networks include phone-call networks [34, 35] and MSN messenger networks [27]. To our best knowledge, this is the first attempt to compare the explicit friend relationship network and implicit activity network. We have analyzed structural characteristics of the activity network and compared them with the friends network. Though the activity network is weighted and directed, its structure is similar to the friend relationship network. We report that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated. When we consider only those links in the activity network that are reciprocated, the degree correlation distribution exhibits much more pronounced assortativity than the friends network and places it close to known social networks. The k-core analysis gives yet another corroborating evidence that the friends network deviates from the known social network and has an unusually large number of highly connected cores. We have delved into the weighted and directed nature of the activity network, and investigated the reciprocity, disparity, and network motifs. We also have observed that peer pressure to stay active online stops building up beyond a certain number of friends. The activity network has shown topological characteristics similar to the friends network, but thanks to its directed and weighted nature, it has allowed us more in-depth analysis of user interaction.

KW - Clustering coefficient

KW - Cyworld

KW - Degree correlation

KW - Degree distribution

KW - Disparity

KW - Friend relationship

KW - Guestbook log

KW - K-core

KW - Network motif

KW - Online social network

KW - Reciprocity

UR - http://www.scopus.com/inward/record.url?scp=63049107220&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=63049107220&partnerID=8YFLogxK

U2 - 10.1145/1452520.1452528

DO - 10.1145/1452520.1452528

M3 - Conference contribution

AN - SCOPUS:63049107220

SN - 9781605583341

SP - 57

EP - 69

BT - Proceedings of the ACM SIGCOMM Internet Measurement Conference, IMC

ER -