Visualizing Dialogue
Visualizing conversations based on themes [Archived]
Research
We further explore conversation visualization as a method of extracting and translating meaning for third party audiences who wish to better understand the interests of conversation participants. In this theme sort, the durations of participants’ contributions begin to illuminate dominant topics across conversation collections, a jumping off point for further analysis and evaluation of our conversation structure, facilitation, and participant dynamics.
Collaborators
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New Social Forms
Exploring new rituals, formats, and structures for coming together
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Storyline
An auditable AI framework for tracing competing narratives across podcasts, conversations, and news
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AI-Assisted Conversation Highlighting
Discovering semantically or emotionally salient moments in spoken discourse using LLMs
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realtalk@Boston
A new civic infrastructure in Boston grounded in dialogue as a way to building “civic muscle” of democracy
Pilots & Programs
Anthology
An AI interface that turns raw conversation audio into interactive maps
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Agora
A training ground to practice consensus-finding with real human perspectives
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