论文标题

影响者会影响吗? - 分析玩家在在线多人游戏中的活动

Do Influencers Influence? -- Analyzing Players' Activity in an Online Multiplayer Game

论文作者

Loria, Enrica, Pirker, Johanna, Drachen, Anders, Marconi, Annapaola

论文摘要

在社会和在线媒体中,传统上将影响者理解为高度可见的人。最近的结果表明,人们可能会模仿有影响力的行为,例如,可以利用营销策略。同样在游戏用户研究领域中,由于对在线影响者的市场营销活动以及保持玩家的参与度,对研究玩家社交网络的兴趣也出现了。尽管这些人具有固有的价值,但仍然很难识别影响者,因为影响者的定义是一个辩论的话题。因此,我们如何识别影响者,他们确实是影响他人行为的个人吗?在这项工作中,我们专注于保留的影响力,以验证中央玩家是否影响了他人在游戏中的永久性。我们确定了由竞争激烈的玩家VS-Player(PVP)多人游戏(坩埚)匹配的社交网络中的中心参与者。然后,我们为每个玩家计算了影响分数,以评估两个连接个体之间的相似性随时间的增加。在本文中,我们能够证明有影响力者的传统指标不一定适用于游戏。相反,我们发现,中央球员小组与有影响力的球员群体不同,这些球员定义为具有最高影响力得分的个体。然后,我们提供两组的分析。

In social and online media, influencers have traditionally been understood as highly visible individuals. Recent outcomes suggest that people are likely to mimic influencers' behavior, which can be exploited, for instance, in marketing strategies. Also in the Games User Research field, the interest in studying player social networks has emerged due to the heavy reliance on online influencers in marketing campaigns for games, as well as in keeping players engaged. Despite the inherent value of those individuals, it is still difficult to identify influencers, as the definition of influencers is a debated topic. Thus, how can we identify influencers, and are they indeed the individuals impacting others' behavior? In this work, we focus on influence in retention to verify whether central players impacted others' permanence in the game. We identified the central players in the social network built from the competitive player-vs-player (PvP) multiplayer (Crucible) matches in the online shooter Destiny. Then, we computed influence scores for each player evaluating the increase in similarity over time between two connected individuals. In this paper, we were able to show the first indications that the traditional metrics for influencers do not necessarily apply for games. On the contrary, we found that the group of central players was distinct from the group of influential players, defined as the individuals with the highest influence scores. Then, we provide an analysis of the two groups.

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