  Bluesky is a nascent ``Twitter-like'' and decentralized social media network
with novel features and unprecedented data access. This paper provides a
characterization of the network, studying the political leaning, polarization,
network structure, and algorithmic curation mechanisms of five million users.
The dataset spans from the website's first release in February of 2023. Users
of the new social media site are predominantly left-center leaning and share
little to no links associated with questionable sources. In contrast to the
homogeneous political stance, we find significant issues-based divergence by
studying opinions related to the Israel-Palestine conflict. Two clear
homophilic clusters emerge: Pro-Palestinian voices make up the plurality of
messages related to the conflict and the proportion has increased with a
lessening of interest. We investigate multiple layers of the multi-scale
Bluesky network based on replies, likes, reposts, and follows, highlighting
differences and similarities between the layers. We differentiate between
persistent and non-persistent interactions and measure metrics of network
topology over time. All networks are heavy-tailed, clustered, and connected by
short paths. We showcase all feeds - algorithmic content recommenders - created
for and by users. A large number of custom feeds have been created but their
uptake by users is limited. Multiple popular feeds aim to provide similar feeds
that are neither topical nor chronological. We conclude by claiming that
Bluesky - for all its novel features - is very similar in terms of its network
structure to existing and larger social media sites and provides unprecedented
research opportunities for social scientists, network scientists, and political
scientists alike.
