Research Lab
News Bridge studied how the language that a media outlet – PBS’ Frontline – uses to promote its content influences the political diversity of its audience. In this project we tracked user engagement with tweets posted by Frontline over three years and built models that, given the tweet text, predict the political diversity of the audience. We then integrated the models into a web app that helped Frontline craft tweets engaging to a politically diverse audience, guided by the model predictions. While studies of political polarization on social media typically investigate the behaviors of individual users, New Bridge focused on the media outlets’ impact on audience fragmentation and developed tools that can help them reduce it. We believe this approach can be further developed and generalized into tools to help communicators (e.g., in public health) engage audiences across political, social, and/or cultural boundaries.
An AI interface that turns raw conversation audio into interactive maps
Research
An LLM-Powered Framework for Analyzing Collective Idea Evolution and Voting Dynamics in Deliberative Assemblies
Research
Supporting decision makers in effective and efficient constituency-informed, AI-supported decision-making. Communicating how constituen...
Research
A curated social experience that transforms dinner between strangers into an opportunity to reimagine how we listen, speak, and share
Research
Over 40 young people participated in a social listening experiment exploring how personal experiences build bridges to better understanding current events and creating mo
Pilots & Programs
A new civic infrastructure in Boston grounded in dialogue as a way to building “civic muscle” of democracy
Pilots & Programs