Emma Spiro
Bio
Dr. Emma S. Spiro is an Associate Professor at the University of Washington Information School, an Adjunct Associate Professor in the Department of Sociology, and an affiliate of the UW Center for Statistics and the Social Sciences. Dr. Spiro is a Data Science Fellow at the eScience Institute at UW. At the UW iSchool Dr. Spiro is co-director of the Social Media Lab (SoMeLab). She is also co-founder and current co-director of the Data Science and Analytics Lab (DataLab). She recently co-founded the Center for an Informed Public (CIP) at UW; the CIP is a collaborative, multi-disciplinary effort that brings together faculty, staff, students and community partners in service of a core mission aiming to resist strategic misinformation and strengthen democratic discourse. Dr. Spiro studies online communication and information-related behaviors in the context of emergencies and disaster events. Recently, she has focused on investigating misinformation online. Her work also explores the structure and dynamics of interpersonal and organizational networks in both online and offline environments. Dr. Spiro’s work has been funded by the National Science Foundation, the Army Research Office, and through other gifts. Her research has been published in PNAS, Social Networks, Field Methods, Demography and Information, Communication & Society, as well as in premier conferences such as the International Conference on Web and Social Media (ICWSM), the ACM CHI Conference on Human Factors in Computing Systems, and the ACM Conference on Computer-Supported Cooperative Work and Social Computing (CSCW). Dr. Spiro earned her Ph.D. in Sociology from the University of California, Irvine. She also holds a B.A. in Applied Mathematics and a B.A. in Science, Technology, and Society from Pomona College, as well as an M.A. from the Institute for Mathematical Behavioral Sciences at the University of California, Irvine.
Preprints
AI-Paraphrasing Increases Perceptions of Social Consensus & Belief in False Information
Yiwei Xu, Emma Spiro, Saloni Dash
Large Language Models (LLMs) have the potential to enhance message features and exploit cognitive heuristics to increase the persuasiveness of strategic…
Repeat Spreaders and Election Delegitimization: A Comprehensive Dataset of Misinformation Tweets from the 2020 U.S. Election
Emma Spiro, Joseph Scott Schafer, Ian Kennedy, Isabella Garcia-Camargo, Kate Starbird, Andrew Beers, Morgan Wack
This paper introduces and presents a first analysis of a uniquely curated dataset of misinformation, disinformation, and rumors spreading on Twitter about the…
Combining interventions to reduce the spread of viral misinformation
Joseph Bak-Coleman, Morgan Wack, Jevin West, Andrew Beers, Joseph Scott Schafer, Kate Starbird, Ian Kennedy, Emma Spiro
Misinformation online poses a range of threats, from subverting democratic processes to undermining public health measures. Proposed solutions range from…