Esport;
Data-Driven Storytelling;
Dota;
2;
Game Analytics;
Artificial Intelligence;
Machine Learning;
AI;
Broadcasting;
social viewing;
D O I:
10.1145/3391614.3393659
中图分类号:
TP39 [计算机的应用];
学科分类号:
081203 ;
0835 ;
摘要:
Esports (competitive videogames) have grown into a global phenomenon with over 450m viewers and a 1.5bn USD market. Esports broadcasts follow a similar structure to traditional sports. However, due to their virtual nature, a large and detailed amount data is available about in-game actions not currently accessible in traditional sport. This provides an opportunity to incorporate novel insights about complex aspects of gameplay into the audience experience - enabling more in-depth coverage for experienced viewers, and increased accessibility for newcomers. Previous research has only explored a limited range of ways data could be incorporated into esports viewing (e.g. data visualizations post-match) and only a few studies have investigated how the presentation of statistics impacts spectators' experiences and viewing behaviors. We present Weavr, a companion app that allows audiences to consume data-driven insights during and around esports broadcasts. We report on deployments at two major tournaments, that provide ecologically valid findings about how the app's features were experienced by audiences and their impact on viewing behavior. We discuss implications for the design of second-screen apps for live esports events, and for traditional sports as similar data becomes available for them via improved tracking technologies.
机构:
Virginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USAVirginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Zhang, Yao
Ramanathan, Arvind
论文数: 0引用数: 0
h-index: 0
机构:
Oak Ridge Natl Lab, Oak Ridge, TN USAVirginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Ramanathan, Arvind
Vullikanti, Anil
论文数: 0引用数: 0
h-index: 0
机构:
Virginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Virginia Tech, Biocomplex Inst, Blacksburg, VA USAVirginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Vullikanti, Anil
Pullum, Laura
论文数: 0引用数: 0
h-index: 0
机构:
Oak Ridge Natl Lab, Oak Ridge, TN USAVirginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Pullum, Laura
Prakash, B. Aditya
论文数: 0引用数: 0
h-index: 0
机构:
Virginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USAVirginia Tech, Dept Comp Sci, Blacksburg, VA 24061 USA
Prakash, B. Aditya
2017 17TH IEEE INTERNATIONAL CONFERENCE ON DATA MINING (ICDM),
2017,
: 615
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624