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The Social Behaviors of Experts in Massive Multiplayer Online Role-Playing Games

机译:大型多人在线角色播放游戏专家的社会行为

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We examine the social behaviors of game experts in Everquest II, a popular massive multiplayer online role-playing game (MMO). We rely on Exponential Random Graph Models (ERGM) to examine the anonymous privacy-protected social networks of 1,457 players over a five-day period. We find that those who achieve the most in the game send and receive more communication, while those who perform the most efficiently at the game show no difference in communication behavior from other players. Both achievement and performance experts tend to communicate with those at similar expertise levels, and higher-level experts are more likely to receive communication from other players.
机译:我们在Everquest II中审视了游戏专家的社会行为,这是一个受欢迎的大型多人在线角色扮演游戏(MMO)。我们依靠指数随机图模型(ERGM)来检查五天期间匿名隐私保护的社交网络1,457名球员。我们发现那些在游戏中实现最多的人发送和接收更多沟通,而那些在游戏中最有效地执行的人则显示来自其他玩家的通信行为的差异。成就和绩效专家往往与类似专业知识水平的人沟通,更高级别的专家更有可能从其他球员接受沟通。

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