Understanding co-evolution in large multi-relational social networks

Ayush Singhal, Atanu Roy, Jaideep Srivastava

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

5 Citations (Scopus)

Abstract

Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs1 have created social networking data at an unprecedented scale. Sony's Everquest II is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting the network into smaller portions for studying the dynamics within these sub-networks, referred to as 'communities'. From an evolutionary perspective of multi-relational network analysis, we have made the following contributions. Specifically, we formulated and analyzed various metrics to capture evolutionary properties of networks. We find that co-evolution rates in trust based 'communities' are approximately 60% higher than the trade based 'communities'. We also find that the trust and trade connections within the 'communities' reduce as their size increases. Finally, we study the interrelation between the dynamics of trade and trust within 'communities' and find interesting results about the precursor relationship between the trade and the trust dynamics within the 'communities'.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages733-740
Number of pages8
ISBN (Print)9781479958801
DOIs
Publication statusPublished - 27 Feb 2014
Externally publishedYes
Event15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014 - San Francisco, United States
Duration: 13 Aug 201415 Aug 2014

Other

Other15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014
CountryUnited States
CitySan Francisco
Period13/8/1415/8/14

Fingerprint

Electric network analysis

ASJC Scopus subject areas

  • Information Systems

Cite this

Singhal, A., Roy, A., & Srivastava, J. (2014). Understanding co-evolution in large multi-relational social networks. In Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014 (pp. 733-740). [7051962] Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/IRI.2014.7051962

Understanding co-evolution in large multi-relational social networks. / Singhal, Ayush; Roy, Atanu; Srivastava, Jaideep.

Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 733-740 7051962.

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

Singhal, A, Roy, A & Srivastava, J 2014, Understanding co-evolution in large multi-relational social networks. in Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014., 7051962, Institute of Electrical and Electronics Engineers Inc., pp. 733-740, 15th IEEE International Conference on Information Reuse and Integration, IEEE IRI 2014, San Francisco, United States, 13/8/14. https://doi.org/10.1109/IRI.2014.7051962
Singhal A, Roy A, Srivastava J. Understanding co-evolution in large multi-relational social networks. In Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. Institute of Electrical and Electronics Engineers Inc. 2014. p. 733-740. 7051962 https://doi.org/10.1109/IRI.2014.7051962
Singhal, Ayush ; Roy, Atanu ; Srivastava, Jaideep. / Understanding co-evolution in large multi-relational social networks. Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014. Institute of Electrical and Electronics Engineers Inc., 2014. pp. 733-740
@inproceedings{bab12b9eab504e7ba22425e13c9ee100,
title = "Understanding co-evolution in large multi-relational social networks",
abstract = "Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs1 have created social networking data at an unprecedented scale. Sony's Everquest II is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting the network into smaller portions for studying the dynamics within these sub-networks, referred to as 'communities'. From an evolutionary perspective of multi-relational network analysis, we have made the following contributions. Specifically, we formulated and analyzed various metrics to capture evolutionary properties of networks. We find that co-evolution rates in trust based 'communities' are approximately 60{\%} higher than the trade based 'communities'. We also find that the trust and trade connections within the 'communities' reduce as their size increases. Finally, we study the interrelation between the dynamics of trade and trust within 'communities' and find interesting results about the precursor relationship between the trade and the trust dynamics within the 'communities'.",
author = "Ayush Singhal and Atanu Roy and Jaideep Srivastava",
year = "2014",
month = "2",
day = "27",
doi = "10.1109/IRI.2014.7051962",
language = "English",
isbn = "9781479958801",
pages = "733--740",
booktitle = "Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",

}

TY - GEN

T1 - Understanding co-evolution in large multi-relational social networks

AU - Singhal, Ayush

AU - Roy, Atanu

AU - Srivastava, Jaideep

PY - 2014/2/27

Y1 - 2014/2/27

N2 - Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs1 have created social networking data at an unprecedented scale. Sony's Everquest II is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting the network into smaller portions for studying the dynamics within these sub-networks, referred to as 'communities'. From an evolutionary perspective of multi-relational network analysis, we have made the following contributions. Specifically, we formulated and analyzed various metrics to capture evolutionary properties of networks. We find that co-evolution rates in trust based 'communities' are approximately 60% higher than the trade based 'communities'. We also find that the trust and trade connections within the 'communities' reduce as their size increases. Finally, we study the interrelation between the dynamics of trade and trust within 'communities' and find interesting results about the precursor relationship between the trade and the trust dynamics within the 'communities'.

AB - Understanding dynamics of evolution in large social networks is an important problem. In this paper, we characterize evolution in large multi-relational social networks. The proliferation of online media such as Twitter, Facebook, Orkut and MMORPGs1 have created social networking data at an unprecedented scale. Sony's Everquest II is one such example. We used game multi-relational networks to reveal the dynamics of evolution in a multi-relational setting by macroscopic study of the game network. Macroscopic analysis involves fragmenting the network into smaller portions for studying the dynamics within these sub-networks, referred to as 'communities'. From an evolutionary perspective of multi-relational network analysis, we have made the following contributions. Specifically, we formulated and analyzed various metrics to capture evolutionary properties of networks. We find that co-evolution rates in trust based 'communities' are approximately 60% higher than the trade based 'communities'. We also find that the trust and trade connections within the 'communities' reduce as their size increases. Finally, we study the interrelation between the dynamics of trade and trust within 'communities' and find interesting results about the precursor relationship between the trade and the trust dynamics within the 'communities'.

UR - http://www.scopus.com/inward/record.url?scp=84946687325&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84946687325&partnerID=8YFLogxK

U2 - 10.1109/IRI.2014.7051962

DO - 10.1109/IRI.2014.7051962

M3 - Conference contribution

AN - SCOPUS:84946687325

SN - 9781479958801

SP - 733

EP - 740

BT - Proceedings of the 2014 IEEE 15th International Conference on Information Reuse and Integration, IEEE IRI 2014

PB - Institute of Electrical and Electronics Engineers Inc.

ER -