Transfeminine users on Bluesky are subject to a transmisogynistic politics of disposability. This manifests, either directly or indirectly, in intracommunity attacks that often end with the target ostracized from the community. We argue that these attacks are driven by on-platformm, distributed folklore that evolves emergently within the social network, aided by platform affordances.
Using our A Blue Start dataset, which combines a higher-order Bluesky starter pack network with a dyadic following network, we want to figure out whether running influence maximization on a hypergraph (i.e. the starter pack network) can empirically also produce a highly influential set of seed nodes for spreading processes on the dyadic following network.
We combine a higher-order dataset (Bluesky starter packs, which are user-created collections of accounts that other users can then follow en masse with one click) with a dyadic dataset (the Bluesky following network) in a dataset paper. The dataset is available on SOMAR at ICPSR, and we have a preprint of the dataset paper on arXiv.
Most Americans don’t follow political accounts on Twitter and see very little political content on average. However, 55% of Americans are worn out by the amount of political content they see on social media. Why? Political content spikes after key events, even (especially) in seemingly apolitical spaces.