Analyzing dynamics of peer-to-peer communication: from questionnaire surveys to agent-based simulation

Authors:
Shinako Matsuyama;Takao Terano
Affiliations:
Dept. Computational Intelligence and Systems Sciences, Tokyo Institute of Technology, Yokohama, Japan and Sony Corporation, Tokyo, Japan;Dept. Computational Intelligence and Systems Sciences, Tokyo Institute of Technology, Yokohama, Japan
Venue:
MABS'06 Proceedings of the 2006 international conference on Multi-agent-based simulation VII
Year:
2006

Citing 4
Cited 1

Small worlds: the dynamics of networks between order and randomness

Small worlds: the dynamics of networks between order and randomness
Linked

Linked
Dynamics of social networks

Complexity - Complex Adaptive systems: Part I
Multi-agent modeling of peer to peer communication with scale-free and small-world properties

KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part IV

The Network Game: Analyzing Network-Formation and Interaction Strategies in Tandem

WI-IAT '08 Proceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 02

Quantified Score

Hi-index	0.00

Visualization

Abstract

This paper discusses dynamic properties of peer-to-peer communication networks, which emerge from information exchanges among people. First, we gather activity data of communication among people through questionnaires in order to categorize both information (contents) and people, then we develop agent-based simulation models to examine implicit mechanisms behind the dynamics. The agent-based models enable us to discover the quality of information exchanged and the preferences of specific communication groups. The simulation results have suggested that 1) peer-to-peer communication networks have scale-free and small world properties, 2) the characteristics of contents and users are observed in word-of-mouth communications, and 3) the combination of real survey data and agent-based simulation is effective.