CommunityData:Twitch: Difference between revisions
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Revision as of 21:00, 9 November 2017
We have an opportunity to study Twitch. For now, lets collect ideas and references that might be useful on this page.
Ideas
Community governance
How do streamers balance competing interests?
A list of possible interests:
- community expressiveness (free speech, interacting with the community)
- entertainment
- control over the community
- attracting / pleasing advertisers
- attracting / pleasing donors
- compliance with platform requirements
- attracting and maintaining a community
Streamer success
Can we predict which channels will take off?
Theories of streamer success:
- Density dependence (prediction: those among the first to stream a game or activity in the early stages of the game's popularity will succeed)
- Resource partitioning (prediction: those who differentiate from others streaming the same game or activity can also succeed)
- Density dependence and resource partitioning looking at viewer overlaps.
- Cross-site communities (those who active in another community will succeed (search gaming sites, forums, reddit, youtube, for evidence)
- Preferential attachment (prediction: those who get popular quicker get more popular)
- Stage / development model (What is important may vary along developmental trajectories)
- Mutualism: Streamers who enter mutualistic relationships with one another (have their communities spam their faces, advertise for one another, show the other's stream on their channel) will be more successful.
Interaction on Twitch
How does Twitch produce
