Using provenance and replay for qualitative analysis of gameplay sessions

IF 2.8 3区 计算机科学 Q2 COMPUTER SCIENCE, CYBERNETICS
Leonardo Thurler, Sidney Melo, Leonardo Murta, Troy Kohwalter, Esteban Clua
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引用次数: 0

Abstract

There is an increasing interest to use game telemetry for analyzing gameplay sessions, with numerous techniques created to help game developers analyze different game aspects like game balancing and behavioral analysis. Among different gameplay session analysis techniques, the collection of provenance data has stood out due to a crucial advantage of this approach: the possibility to identify cause–effect relationships between game events. In previous work, we presented our conceptual framework called Prov-Replay, which provides a replay synchronized with an interactive provenance graph visualization. We validate Prov-Replay by creating PinGU Replay, a tool that implements our conceptual framework and applied it in a commercial game. Due to the promising results, this paper extends our previous work by presenting a detailed overview about Prov-Replay implementation, introducing a new feature that provides an analysis dashboard, and applying our experiment methodology to a new commercial game. We also enhance the concept of analytics related to provenance through the replay pipeline. Finally, we made PinGU Replay available as open-source software. Our new experiment results reinforce that, when using our conceptual framework fundamentals, it is possible to improve the efficiency and effectiveness of qualitative analysis process.

利用来源和回放对游戏过程进行定性分析
人们对使用游戏遥测技术分析游戏会话的兴趣与日俱增,并创造了许多技术来帮助游戏开发人员分析游戏的不同方面,如游戏平衡和行为分析。在各种游戏会话分析技术中,源数据收集技术脱颖而出,因为这种方法有一个重要优势:可以识别游戏事件之间的因果关系。在之前的工作中,我们介绍了名为 Prov-Replay 的概念框架,该框架提供了与交互式出处图可视化同步的回放。我们通过创建 PinGU Replay 验证了 Prov-Replay,该工具实现了我们的概念框架,并将其应用于一款商业游戏。由于取得了可喜的成果,本文扩展了我们之前的工作,详细介绍了 Prov-Replay 的实现,引入了提供分析仪表板的新功能,并将我们的实验方法应用到了一款新的商业游戏中。我们还通过重放管道加强了与出处相关的分析概念。最后,我们将 PinGU Replay 作为开源软件提供。我们的新实验结果证明,使用我们的概念框架基础,可以提高定性分析过程的效率和效果。
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来源期刊
Entertainment Computing
Entertainment Computing Computer Science-Human-Computer Interaction
CiteScore
5.90
自引率
7.10%
发文量
66
期刊介绍: Entertainment Computing publishes original, peer-reviewed research articles and serves as a forum for stimulating and disseminating innovative research ideas, emerging technologies, empirical investigations, state-of-the-art methods and tools in all aspects of digital entertainment, new media, entertainment computing, gaming, robotics, toys and applications among researchers, engineers, social scientists, artists and practitioners. Theoretical, technical, empirical, survey articles and case studies are all appropriate to the journal.
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