Conversation

basically the way this works is, if you're in the top 1% of Twitter users by following count, You're an influencer. The rest of us users are classified into SimClusters based on which influencers we follow in common. This clustering is done before tweets are delivered to users.
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That's what they mean by a heterogeneous representation: Your TL is literally different than other peoples. You're trapped in a bubble based on which influencers you follow. This creates the phenomenon known as "ingroup", among others
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Replying to and
it's very much an estimate, based on numbers in the paper and the power law dynamics of Twitter users. and i made that estimate back in 2020 when the paper came out, so i don't know how much those numbers have changed since then. but a useful heuristic i think
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