Name
Abstract | ||
|---|---|---|
Large-scale streaming platforms such as Twitch are becoming increasingly popular, but detailed audience-streamer interaction dynamics remain unexplored at scale. In this paper, we perform a mixed methods study on a dataset with over 12 million audience chat messages and 45 hours of streamed video to understand audience participation and streamer performance on Twitch. We uncover five types of streams based on size and audience participation styles, from small streams with close streamer-audience interactions to massive streams with the stadium-style audiences. We discuss challenges and opportunities emerging for streamers and audiences from each style and conclude by providing data-backed design implications that empower streamers, audiences, live streaming platforms, and game designers.
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Year | DOI | Venue |
|---|---|---|
2019 | 10.1145/3342220.3344926 | Proceedings of the 30th ACM Conference on Hypertext and Social Media |
Keywords | Field | DocType |
audience participation, data analysis, games, twitch | World Wide Web,Computer science,Multimedia | Conference |
ISBN | Citations | PageRank |
978-1-4503-6885-8 | 0 | 0.34 |
References | Authors | |
0 | 6 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Claudia Flores-Saviaga | 1 | 0 | 0.34 |
| Jessica Hammer | 2 | 68 | 25.95 |
| Juan Pablo Flores | 3 | 0 | 0.68 |
| Joseph Seering | 4 | 28 | 7.68 |
| Stuart Reeves | 5 | 871 | 66.81 |
| Saiph Savage | 6 | 104 | 16.32 |