Two grad students and I are doing research on #mastodon and "the politics of federation," and so far for data/materials, we've collected: interviews with admins, 70 Masto threads on the topic, dozens of blog posts, and ~170 Masto CoC statements. It seems like a lot, but... what are we missing? Suggestions welcome!
@robertwgehl Random sample of tweets with matched random sample of toots from several different time periods (e.g. around major news events, etc.), label tweets and toots with metadata like "supports alt-right or Nazi philosophy", "contains racial slur," etc. and compare samples
@bgcarlisle Not a bad idea! With the right coding scheme, that may reveal distinctions in terms of populations. Question, though: what's a random sample in Masto, given that any 1 entry point may not federate with all others?
@robertwgehl Take the list of instances from joinmastodon.com and choose a sample of toots weighted by the number of users or toots on that instance
@robertwgehl Other things you could possible code for:
* Does the post contain actual original content?
* Is the post a link to a news source with commentary?
* Is this a hot take on the topic of discussion du jour?
* Is the user posting this identified as a bot?
* Does the user claim to be an individual or a Brand™?
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