Visualizing meaning and participation at scale in Decidim data with cosmos.gl

Tracing participation and text contributions at scale within any Decidim instance reveals meaningful emergent patterns. Visualizing proposal and comment data as contribution networks and semantic clusters can enable our understanding of how participation and priorities evolve over time.

By combining powerful interactive visualization (cosmos.gl) and topic modeling (BERTopic) techniques, using open multilingual LLMs, we can reconstruct a wide, dynamic and context-rich view of any Decidim instance, showing how participation is articulated and fluctuates across topics and processes.

This talk aims to showcase large scale visualization of Decidim data in different languages and contexts, as well as to advance the community conversation on how to incorporate sense-making and network analysis tools as reflective interfaces for a shared understanding of collective priorities.

Demos:
Tracing topics within Decidim Barcelona
Networks VS embeddings visualization Decidim Barcelona

Language: English