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Excited to share our #UIST2022 paper introducing FeedLens, a novel system that repurposes people’s research paper feeds on Semantic Scholar as lenses. Without any additional training, these lenses show relevance for all types of related entities, like authors and institutions. 🧵 
Say you have 2 research paper feeds on the topics Interpretability and Mental Models. Using FeedLens, you can view the entities in any content list on Semantic Scholar (e.g., papers and authors in search results or author homepages) based on their relevance to your research feeds
FeedLens uses the simple yet powerful polymorphic lenses technique, which converts a lens based on one entity (e.g., research papers) into a polymorphic lens that can be applied to any type or collection of entities in a knowledge graph (e.g., authors, institutions, conferences)
How might an online community look after many people join? My paper w/ @lindsaypopowski @Carryveggies @merrierm @percyliang @msbernst introduces "social simulacra": a method of generating compelling social behaviors to prototype social designs 🧵
arxiv.org/abs/2208.04024 #uist2022
arxiv.org/abs/2208.04024 #uist2022
You can see some of its generated behaviors—posts, replies, trolls—in our demo here: social-simulacra.herokuapp.com
E.g., say you are creating a new community for discussing a StarWar game with a few rules. Given this description, our tool generated a simulacrum like this: (2/10)
E.g., say you are creating a new community for discussing a StarWar game with a few rules. Given this description, our tool generated a simulacrum like this: (2/10)
Why are these useful? In social computing design, understanding our design decisions’ impact is hard since many challenges do not arise until a system is populated by *many*. Think about: newcomers with unintentional norm-breaking, trolling, or other antisocial behaviors (3/10)
