Guns and guardians: Comparative cluster analysis and behavioral profiling in destiny

Anders Drachen, James Green, Chester Gray, Elie Harik, Patty Lu, R. Sifa, D. Klabjan
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引用次数: 24

Abstract

Behavioral profiling in digital games with persistent online worlds are vital for a variety of tasks ranging from understanding the player community to informing design and business decisions. In this paper behavioral profiles are developed for the online multiplayer shooter/role-playing game Destiny, the most expensive game to be launched to date and a unique hybrid incorporating designs from multiple traditional genres. The profiles are based on playstyle features covering a total of 41 features and over 4,800 randomly selected players at the highest level in the game. Four clustering models were applied (k-means, Gaussian mixture models, k-maxoids and Archetype Analysis) across the two primary game modes in Destiny: Player-versus-Player and Player-versus-Environment. The performance of each model is described and cross-model analysis is used to identify four to five distinct playstyles across each method, using a variety of similarity metrics. Discussion on which model to use in different circumstances is provided. The profiles are translated into design language and the insights they provide into the behavior of Destiny's player base described.
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枪支和监护人:命运中的比较聚类分析和行为分析
在具有持久在线世界的数字游戏中,行为分析对于理解玩家社区、告知设计和商业决策等各种任务都至关重要。本文针对在线多人射击/角色扮演游戏《命运》(Destiny)进行了行为分析,这是迄今为止发行的最昂贵的游戏,也是一款结合了多种传统类型设计的独特混合游戏。这些资料是基于游戏风格特征,涵盖了41个特征和超过4800名随机选择的最高级别玩家。我们将四种聚类模型(k-means,高斯混合模型,k-maxoids和原型分析)应用于《命运》的两种主要游戏模式:玩家对抗玩家和玩家对抗环境。我们描述了每个模型的性能,并使用不同的相似性指标进行跨模型分析,从而在每种方法中识别出4至5种不同的游戏风格。讨论了在不同情况下使用哪种模型。这些配置文件被转化为设计语言,并为《命运》玩家基础的行为提供洞见。
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