Graffiti: Enabling an Ecosystem of Personalized and Interoperable Social Applications
Name
3746059.3747627.pdf
Size
4.8 MB
Format
Adobe PDF
Checksum (MD5)
96b94462788aa87ec136b833e385625d
Author(s)
Henderson, Theia
Karger, David
Clark, David D
Date Issued
September 27, 2025
Publisher
ACM|The 38th Annual ACM Symposium on User Interface Software and Technology
Citation
Theia Henderson, David R. Karger, and David D. Clark. 2025. Graffiti: Enabling an Ecosystem of Personalized and Interoperable Social Applications. In Proceedings of the 38th Annual ACM Symposium on User Interface Software and Technology (UIST '25). Association for Computing Machinery, New York, NY, USA, Article 202, 1–21.
Version
Final published version
Abstract
Most social applications, from Twitter to Wikipedia, have rigid one-size-fits-all designs, but building new social applications is both technically challenging and results in applications that are siloed away from existing communities. We present Graffiti, a system that can be used to build a wide variety of personalized social applications with relative ease that also interoperate with each other. People can freely move between a plurality of designs—each with its own aesthetic, feature set, and moderation—all without losing their friends or data.
Our concept of total reification makes it possible for seemingly contradictory designs, including conflicting moderation rules, to interoperate. Conversely, our concept of channels prevents interoperation from occurring by accident, avoiding context collapse.
Graffiti applications interact through a minimal client-side API, which we show admits at least two decentralized implementations. Above the API, we built a Vue plugin, which we use to develop applications similar to Twitter, Messenger, and Wikipedia using only client-side code. Our case studies explore how these and other novel applications interoperate, as well as the broader ecosystem that Graffiti enables.
Description
UIST ’25, Busan, Republic of Korea
MIT Department
Massachusetts Institute of Technology. Computer Science and Artificial Intelligence Laboratory
Terms of Use
Creative Commons Attribution-ShareAlike
Persistent DSpace Link
DOI of Published Version
https://doi.org/10.1145/3746059.3747627
