Images by Enle Li

Rigorous, Participatory, Public Research

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Our work derives from rigorous application of the scientific method: observation, hypothesis generation, prediction, experimentation, and results analysis, interpretation, and reporting. We strive to bring into awareness and clearly communicate the biases, assumptions, blind spots, and limitations in our methods, data, and findings. And we make our work public, through our partners, on our website, and in peer-reviewed publications.

We always put our expertise in service of the communities and partners we work with, integrating them in every stage of our work, from research design and sampling to interpretation and reporting. And we never compromise our integrity and independence as researchers. We do not accept funding that would require such compromise.

We partner with a wide range of organizations and communities on issues of existential importance, like climate, denuclearization, racial justice, gun safety, immigration, artificial intelligence, and more. One of the first papers we co-authored looked at fracking narratives in documentary film.

Data Platform + Transparent, Principled Data Practices

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Media data live inside media companies, and there are few incentives or precedents for making them available for research. So we’re grateful that Nielsen, Comscore, Peakmetrics, and others donate to us: media consumption panel data for 300,000+ people in the U.S., across broadcast television, streaming, desktop, mobile, and tablet; and media content data, including television closed captions, online news text, social media posts, videos and transcripts from YouTube and Tiktok, metadata, and more. All panelists opt in and are compensated for panel participation, and all data are anonymized prior to ingestion.

By engineering these two kinds of data into one platform, called the Narrative Observatory, we gain a minute-by-minute view into how people (actual people, not bots, hashtags, or inauthentic actors!) move through media content, across sites and devices. We can see patterns in how people engage with media and form into audiences and networks, and in the content they consume and create, all based on media behavior, not survey results.

Our in-house team of engineers and data scientists is vigilant to keep data safe and secure, and, in our reporting, to prevent de-anonymization and protect the communities we work with. We always strive to bring into awareness and clearly communicate the biases, assumptions, blind spots, and limitations in our methods and data, especially when we build models and assemble annotations for models, which we do with annotators we employ directly.

Exploration, Invention, Creativity

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Too much intelligence ends up in difficult to discover white papers on websites, after a single use. We are always experimenting with different formats for delivering intelligence that partners can use, again and again, as tools that elevate their work, and also surprise and delight. This requires a discipline of listening and innovation.

It also requires collaboration. That’s why we have a multi-disciplinary, multi-skilled team, who are not just researchers, data scientists, engineers, and strategists, but also poets, artists, filmmakers, futurists, and other refugees from commercially focused creativity. We maintain a big advisory board, and a growing community of partners and repeat collaborators who regularly contribute to our work.

We support a network of academic researchers too, from leading universities like Brown, George Washington, Stanford, Northeastern, and The Hertie School. They use our data and our secure cloud-based analysis platforms to build basic knowledge and extend our creativity. This helps us keep ahead of rapid developments in media and continue to make research that is widely circulated, impactful and a thing of beauty.