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Network game design: hints and implications of player interaction
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Source Network and System Support for Games archive
Proceedings of 5th ACM SIGCOMM workshop on Network and system support for games table of contents
Singapore
SESSION: Understanding player behavior for game design table of contents
Article No. 17  
Year of Publication: 2006
ISBN:1-59593-589-4
Authors
Kuan-Ta Chen  Institute of Information Science
Chin-Laung Lei  National Taiwan University
Sponsor
SIGCOMM: ACM Special Interest Group on Data Communication
Publisher
ACM  New York, NY, USA
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ABSTRACT

While psychologists analyze network game-playing behavior in terms of players' social interaction and experience, understanding user behavior is equally important to network researchers, because how users act determines how well network systems, such as online games, perform. To gain a better understanding of patterns of player interaction and their implications for game design, we analyze a 1, 356-million-packet trace of ShenZhou Online, a mid-sized commercial MMORPG. This work is dedicated to draw out hints and implications of player interaction patterns, which is inferred from network-level traces, for online games.

We find that the dispersion of players in a virtual world is heavy-tailed, which implies that static and fixed-size partitioning of game worlds is inadequate. Neighbors and teammates tend to be closer to each other in network topology. This property is an advantage, because message delivery between the hosts of interacting players can be faster than between those of unrelated players. In addition, the property can make game playing fairer, since interacting players tend to have similar latencies to their servers. We also find that participants who have a higher degree of social interaction tend to play much longer, and players who are closer in network topology tend to team up for longer periods. This suggests that game designers could increase the "stickiness" of games by encouraging, or even forcing, team playing.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
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Collaborative Colleagues:
Kuan-Ta Chen: colleagues
Chin-Laung Lei: colleagues