The National Science Foundation (NSF) has awarded a $3 million collaborative grant to a team led by the University of Washington’s Center for an Informed Public (CIP) and supported by Stanford University to study ways to apply collaborative, rapid-response research to mitigate online disinformation.
The project, funded through NSF’s Secure and Trustworthy Cyberspace (SaTC) program, will start in October and be led by UW Human Centered Design & Engineering associate professor Kate Starbird and UW Information School associate professors Emma S. Spiro and Jevin D. West, who in 2019 helped launch the Center for an Informed Public, a multidisciplinary research center with a mission to study mis- and disinformation, promote an informed society and support democratic discourse.
Of the $3 million in NSF funding awarded for the UW-Stanford research collaboration, the UW team at the CIP will receive $2.25 million.
“Working to advance scientific understanding of online disinformation, this research will develop and evaluate ‘rapid response’ methods for studying and communicating about disinformation at a sophistication and pace on par with the dynamic and interdisciplinary nature of the challenge,” said Starbird, who will be starting a two-year term as the CIP’s faculty director in mid September.
Through the development and implementation of rapid-response frameworks, the CIP’s research team will quickly identify and analyze disinformation campaigns and communicate those findings uniquely to diverse stakeholders in government, industry, media and the public more broadly, with the aim of building societal resilience to this kind of manipulation.
“We aim not only to support our own internal research, but to develop and share playbooks and toolkits for others to use to create the sociotechnical infrastructure to support these kinds of collaborations,” Spiro said.
The research has three integrated components. First, the research team, led by the CIP in collaboration with Stanford Internet Observatory technical research manager Renée DiResta, will develop models and theories of how disinformation is seeded, cultivated and spread that take into account the sociotechnical nature of the problem. Second, the team will develop and apply rapid-response frameworks for responding to disinformation quickly. And third, the team will evaluate the impact of multi-stakeholder collaborations to address disinformation in real-time during real-world events.
The work will apply a mixed-method approach that integrates novel visualizations and network analysis to identify patterns and anomalies with qualitative analysis that reveals the meanings of those features. Extending from a rapid-response approach, the team, which includes Stanford Department of Communication professor Jeffrey T. Hancock as co-principal investigator, will use interviews and experiments to evaluate strategies for communicating these findings with diverse stakeholders.
Conceptually, this research will leverage theories of rumoring from sociology and social psychology and the growing body of literature related to online manipulation to shed light on the participatory dynamics of disinformation campaigns. In terms of impacts on scientific infrastructure, this effort builds collaboration frameworks that others can use to create their own systems for rapid response.
“Real-time solutions will not rely solely upon automation, but on collaboration,” said West, who has served as the CIP’s inaugural faculty director. “Through our work at the center, we aim to develop the infrastructure — including a roadmap for multi-stakeholder collaborations — to rapidly detect, analyze, and communicate about various information threats in real time, when it matters the most.”
CIP faculty, researchers, students and staff have been involved in previous rapid-response research projects focused on identifying, tracking and responding to mis- and disinformation. In the summer of 2020, the CIP, along with Stanford Internet Observatory, Graphika and the Atlantic Council’s Digital Forensics Research Lab, co-founded the Election Integrity Partnership, a nonpartisan research consortium that monitored and analyzed mis- and disinformation about voting before, during and after the November 2020 U.S. elections and facilitated information exchange among stakeholders in government, media, civil society and at tech platforms. In March 2021, the research consortium published “The Long Fuse: Misinformation and the 2020 Election,” a nearly 300-page report described by former U.S. Cybersecurity and Infrastructure Security Agency director Christopher Krebs as “the seminal report on what happened in 2020, not just the election but also through January 6.”
This year, the CIP has been involved in a similar multi-institution research collaboration, the Virality Project, that’s been tracking and analyzing COVID-19 vaccine misinformation and social media narratives related to vaccine hesitancy.
Since January 2020, the CIP has collected more than 11 billion tweets and more than 100 terabytes of social media data as part of its rapid-response mis- and disinformation research activities.
Starbird, Spiro and West — with UW School of Law professor Ryan Calo and iSchool senior principal research scientist Chris Coward — co-founded the Center for an Informed Public in December 2019 with $5 million in funding from the John S. and James L. Knight Foundation with additional financial support from the William and Flora Hewlett Foundation.
Craig Newmark Philanthropies and Omidyar Network have provided financial support for the CIP’s rapid-response research work, including $1 million in new funding from Newmark to support student researchers — to be known as Craig Newmark Fellows — infrastructure and communication needs around election-related mis- and disinformation.
The CIP will be hiring a research scientist to lead and facilitate the rapid-response research work ahead. CIP-affiliated undergraduate and doctoral student researchers and postdoctoral scholars detailed to this work will participate in rapid data analysis of social media content, learning techniques of data science, including programming skills, database querying, visualization, network analysis and machine-learning approaches in addition to more qualitative skills of open-source research.
