中央研究院  |   資訊科學研究所  |   多媒體網路與系統實驗室 
Network Game Design: Hints and Implications of Player Interaction
(NOTE: Sheng-Wei Chen is also known as Kuan-Ta Chen.)

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.


Citation
Kuan-Ta Chen and Chin-Laung Lei, "Network Game Design: Hints and Implications of Player Interaction," In Proceedings of ACM NetGames 2006, Singapore, Oct 2006.

BibTex
@INPROCEEDINGS{chen06:interaction,
  AUTHOR     = {Kuan-Ta Chen and Chin-Laung Lei},
  TITLE      = {Network Game Design: Hints and Implications of Player Interaction},
  BOOKTITLE  = {Proceedings of ACM NetGames 2006},
  ADDRESS    = {Singapore},
  MONTH      = {Oct},
  YEAR       = {2006}
}
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