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Misinformation, Disinformation, and Crisis Informatics

Speaker: Kate Starbird
Institution: Department of Human Centered Design and Engineering (HCDE), University of Washington
Year: 2020
Video ID: 03UCXMUM3uc

TL;DR

Kate Starbird, associate professor at UW's HCDE and co-founder of the Center for an Informed Public, discusses how misinformation and disinformation spread during crisis events, with case studies from the COVID-19 pandemic and 2020 election. She distinguishes between harmful misinformation (false but well-intentioned), disinformation (deliberately deceptive), and coordinated inauthentic behavior, illustrating how conspiracy theories (5G causing COVID, Bill Gates engineered the virus) embed themselves in physical reality through graffiti and anti-mask protests. Her research, which spans both the prosocial uses of social media during disasters and the malicious spread of rumors, emphasizes that understanding the mechanisms of false information spread requires mixed methods—quantitative social-media analysis alongside qualitative human-centered investigation.

Key claims

Misinformation vs. disinformation: Misinformation is false information spread without malicious intent (the shark-in-flooded-waters meme, the March 2020 grocery-store rumor). Disinformation is deliberately crafted falsehood designed to deceive and manipulate. Both cause real-world harm, but understanding the distinction matters for intervention design.

Crisis events create information vacuums that rumors fill: During natural disasters and pandemics, uncertainty is high and official information is often delayed or incomplete. People naturally reach out to social networks for information, and unverified claims propagate rapidly because they address urgent information needs.

Conspiracy theories can drive physical-world harm: The false claim that COVID-19 was engineered by Bill Gates as a population-control plot manifested as real graffiti ("Bill Gates is a killer") in Seattle neighborhoods. Similarly, anti-mask protests and intentional virus-spreading resulted directly from conspiratorial narratives spreading online.

Science gets weaponized during crisis: People post links to scientific articles to lend credibility to false claims, sometimes citing retracted papers or misinterpreting genuine research to support conspiracy theories (e.g., misusing COVID-19 research to argue the virus was engineered).

Coordinated inauthentic behavior: Beyond organic misinformation, organized actors (bots, amplification networks, state actors) deliberately amplify false narratives to increase polarization and undermine trust in institutions.

Mixed-methods research is essential: Purely quantitative analysis of social-media patterns can miss local, qualitative reality. Starbird's lab combines large-scale data analysis with qualitative interviews, ethnography, and close reading of individual cases to understand how rumors take hold and spread.

Mechanisms discussed

Rumor propagation during crisis: - Information vacuums and uncertainty drive sharing - Clickbait-style rumors (sharks in floodwater) spread for attention and humor - Well-meaning rumors (grocery-store lockdown warning) spread because people want to help friends and family - Conspiracy narratives (5G causes COVID) provide simple explanations for complex, frightening events

Narrative embedding: - Online conspiracy theories cascade into physical-world behavior (protests, graffiti, intentional disease spread) - False claims about vaccines, 5G, and engineered pathogens find receptive audiences during moments of high uncertainty - Politicized narratives emerge that align with pre-existing partisan identities

Institutional response gaps: - Official communications often lag behind rumors - Fact-checking is slow and labor-intensive, while rumors spread at platform velocity - Authority voices (scientists, public health officials) struggle to counteract coordinated misinformation campaigns

Connections

Notes

This talk is valuable for its grounding of misinformation in the lived reality of crisis events. Starbird moves seamlessly between abstract research (network analysis, information diffusion models) and concrete examples (the shark meme, the grocery-store panic, the Bill Gates graffiti she photographed). This concrete-to-abstract movement makes her argument about the real-world stakes of misinformation tangible.

The distinction between misinformation and disinformation is carefully drawn but practical: it affects how we design interventions. Disinformation requires detection and attribution; misinformation requires rapid, authoritative correction and an understanding of why people shared it in the first place.

The observation that conspiracy theories provide simple answers to complex, frightening situations (a pandemic, an election with high stakes) explains their appeal. This insight aligns with psychology research on cognitive closure and uncertainty reduction but is grounded here in concrete pandemic examples.

Starbird's emphasis on mixed methods—combining big-data social-media analysis with qualitative ethnographic understanding—challenges the "algorithms vs. humans" framing that dominated much early platform-accountability discourse. She argues both are needed: you need to see the large-scale cascade and understand the local context in which rumors are believed.

The Center for an Informed Public's founding mission (December 2019) happened just before the pandemic, and the talk reflects the lab's pivot to understanding information flows during COVID-19 and the 2020 election—two concurrent crises that tested the limits of public-information infrastructure.