Viewer types in game live streams: questionnaire development and validation

Abstract

Producing and consuming live-streamed content is a growing trend attracting many people today. While the actual content that is streamed is diverse, one especially popular context is games. Streamers of gaming content broadcast how they play digital or analog games, attracting several thousand viewers at once. Previous scientific work has revealed that different motivations drive people to become viewers, which apparently impacts how they interact with the offered features and which streamers’ behaviors they appreciate. In this paper, we wanted to understand whether viewers’ motivations can be formulated as viewer types and systematically measured. We present an exploratory factor analysis (followed by a validation study) with which we developed a 25-item questionnaire assessing five different viewer types. In addition, we analyzed the predictive validity of the viewer types for existing and potential live stream features. We were able to show that a relationship between the assessed viewer type and preferences for streamers’ behaviors and features in a stream exists, which can guide fellow researchers and streamers to understand viewers better and potentially provide more suitable experiences.