Bluesky starter packs reveal tight topical and social connections
Who Belongs Together? Topical and Social Structure in Bluesky Starter Packs
Social and Information NetworksComputers and Society
Summary
Starter packs on Bluesky are curated groups of accounts meant to help new users find communities. The authors studied over 2700 packs and found that members share similar topics, interests, and social connections, making the packs meaningful groups. They also found that the people creating these packs tend to have interests like the members. However, not all followers of pack members follow many others in the same pack, so there is still room to discover more accounts. This suggests that human-made collections like these can help online communities grow and can complement computer-made recommendations.
What this means in practice
- •For social media platform designers: Design recommendation systems that integrate human-curated collections to improve community discovery and user onboarding.
- •For online community managers: Create curated account groups to foster stronger topical and social network cohesion among community members.
Authors
Sima Adleyba, Onur Varol
Abstract
Bluesky starter packs are human curated collections of accounts and feeds aimed at helping users discover new communities, especially during onboarding. Prior research has examined their effects on platform growth and account visibility. However, whether these packs capture meaningful topical and social structure remains unanswered. We study 2718 active starter packs containing approximately 144K accounts, combining pack metadata, follow graphs, user post histories and inferred demographic attributes to answer this question. We assign starter packs to 17 topical categories, and examine semantic coherence, curator--member resemblance, shared audiences, and follow reciprocity. We found that pack members are closely aligned with both their fellow pack members and their pack's description compared to accounts included in other packs of the same topic, indicating topical specificity beyond the broader topical categories. We also identify semantic resemblance between curators and their pack members, while demographic resemblance varies by attribute and topic. Network analyses show higher follow reciprocity among members of the same pack and between members and curators than between a pack member and either another member from the same broader topic or a nonmember. Members also share substantial portions of their follower networks with fellow pack members. Despite this coherence, a typical member's follower follows only a small fraction of other members in the pack, indicating limited audience coverage. These results suggest that starter packs capture coherent topical and social groups while leaving opportunities for further account discovery. More broadly, results show human-curation can be useful to capture relevant communities and connections, and platforms could integrate human-curation into recommendation systems as a complement to algorithmic systems to expand opportunities for discovery.