CrowdChess: A System to Investigate Shared Game Control in Live-Streams

Pascal Lessel; Alexander Vielhauer; Antonio Krüger

In: Proceedings of the Annual Symposium on Computer-Human Interaction in Play. ACM SIGCHI Annual Symposium On Computer-Human Interaction in Play (CHI Play-17), Amsterdam, Netherlands, Pages 389-400, ISBN 978-1-4503-4898-0, ACM, 2017.


Recently, gaming live-streams appeared in which the audience interacts without a streamer. These settings sometimes allow the audience to select from a set of input aggregators to mediate how individual contributions are aggregated. We developed CrowdChess, a system which is optimized for the live-streaming context: multiple viewers play chess together in a single game instance against an AI; they suggest moves and further select one of six aggregators to mediate their contributions. In contrast to existing approaches, CrowdChess allows reasoning about the quality of individual and aggregator contributions, and thus it serves as a test bed for how effectively an audience interacts in such settings. We conducted a study in a live-streaming setup (n=12) and contribute insights on the player perception of audience-driven games and show how aggregators in such a small-scale setting are used, for example, the tendency to use group-based aggregators instead of empowering an individual.

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Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence