Influence of Virtual Tipping and Collection Rate in Social Live Streaming Services

Ueki, Shintaro; Toriumi, Fujio; Sugawara, Toshiharu

doi:10.1007/978-3-031-53503-1_10

Cited by 2 publications

(2 citation statements)

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Section: Related Workmentioning

confidence: 99%

“…Among studies considering monetary rewards, Ueki et al [13,31] adopted a gametheoretical model to explore the impact of monetary rewards. However, they assumed that monetary rewards are provided by a platformer to increase activities [13] or that the experiments are limited to artificial networks [31]. Therefore, we conducted extensive experiments on real-world networks collected from Facebook and Twitch, comparing the results between artificial and realistic networks.…”

Section: Related Workmentioning

confidence: 99%

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Game-Theoretic Implications for Uncovering the Effects of Virtual Tipping in Complex User Networks

Ueki,

Toriumi,

Sugawara

2024

Preprint

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Consumer-generated media (CGM), including social live streaming service (SLSS), often incorporate gamification elements to engage users. Online virtual tips and gifts, such as ”bits” in Twitch, exemplify this approach by fostering interactive dynamics between live streamers and their audience. However, issues remain in understanding the impact of (virtual) tips on user behavior and how platform commissions, which are partly collected from the tips provided by other users, influence the platform’s overall revenue and user behavioral strategies. This study considers a CGM/SLSS platform, such as Twitch, as a variation of the public goods game and proposes a game-theoretical model integrated with a platform-mediated tipping system with a certain commission rate. In experiments , the proposed model was applied to artificial and actual SLSS networks, demonstrating that the influence of a tipping system on user behavior is significant , impacting the motivation for live streaming and the effort to improve its quality. Depending on individual preferences for psychological or monetary reward, the commission rate is determined by the platform depending on the users’ network positions, such as the degree of connectivity, which corresponds to the number of followers/followees in SLSS networks. Our findings offer valuable insights into the design and management of SLSS platforms and further suggest that there may be an appropriate commission rate to maximize platform revenue.

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