Live streaming has enabled eSports to become more accessible, ranging from professionally organized tournaments to individuals hosting from their bedroom. While different aspects of eSports have been investigated in separate contexts, in this article, we report findings of two survey studies to explore eSports as a holistic media ecosystem that includes playing, streaming, viewing, and spending. Study 1 looks at cross-platform patterns between playing and spending within the game as well as between viewing, streaming, and spending on live streaming platforms in the context of Fortnite. Study 2 examines the relationships between viewing and spending patterns on live streaming platforms. Results indicate that playing, viewing, and in-game spending are strongly related. Yet none of these behavioral metrics explain why people spend money on live streaming platforms to support streamers. Rather, psychological factors such as emotional attachment to the streamer and appreciation of the streamers’ talents are what drive streamer support.
Driven by state-of-the-art AI technologies, human-AI collaboration has become an important area in computer-supported teamwork research. While human-AI collaboration has been investigated in various domains, more research is needed to explore human perceptions and expectations of AI teammates in human-AI teaming. To achieve an in-depth understanding of how people perceive AI teammates and what they expect from AI teammates in human-AI teaming, we conducted a survey with 213 participants and a follow-up interview with 20 participants. Considering the context-dependency of teamwork, we chose to study human-AI teaming in the context of multiplayer online games as a case study. This study shows that people have mixed feelings toward AI teammates but hold a positive attitude toward future collaboration with AI teammates in general. Our findings highlight people's expectations for AI teammates in a rapidly changing collaborative environment (e.g., instrumental skills for in-game tasks, shared understanding between humans and AI, communication capabilities, human-like behaviors and performance), as well as factors that impact people's willingness to team up with AI teammates (e.g., pre-existing attitudes toward AI, previous collaboration experience with humans). We contribute to CSCW by shedding light on how AI should be structured in human-AI teaming to support highly complex collaborative activities in CSCW environments.
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