DUB Seminar will be conducted using Zoom, via an invitation distributed to the DUB mailing list. Participants who are logged into Zoom using a UW account will be directly admitted, and participants who are not logged in to a UW account will be admitted using a Zoom waiting room.
There will not be a publicly-available video of this DUB seminar.
Online social media platforms have brought numerous positive changes, including access to vast amounts of news and information. Yet, those very opportunities have created new challenges—our information ecosystem is now rife with problematic content, ranging from misinformation, conspiracy theories, to hateful and incendiary propaganda. As a social computing researcher, my work introduces computational methods and systems to understand and design defenses against such problematic online content. In this talk, I will focus on two aspects of problematic online information: 1) conspiracy theories, and 2) extremist propaganda.
First, leveraging 10 years of discussion data spanning millions of conspiratorial posts on Reddit, I will present scalable methods to determine the recurring elements underlying these discussions and ways to unravel what causes users to join conspiratorial communities. Second, I will dive into a special type of problematic content: narratives of extremist hate groups. Merging framing theory from social movement research with big data analyses, I will discuss the ecosystem of cross-platform communication by hate groups. Finally, I will close by previewing important new opportunities I see my lab tackling in the next five years to address some of these problems, including conducting social audits to defend against algorithmically generated misinformation, building human- machine mixed initiative systems for assessing credibility, and designing socio-technical interventions and systems to promote online trust.
Tanu Mitra is an Assistant Professor at the Information School at University of Washington, where she leads the Social Computing research group. Her research focuses on studying and building large-scale social computing systems to understand and counter problematic information online. Her work employs a range of interdisciplinary methods from the fields of human computer interaction, data mining, machine learning, and natural language processing. Tanu’s work has been supported by grants from NSF, Social Science One, and DoD.
Her research has been recognized through multiple awards and honors, including an NSF-CRII award and the Virginia Tech College of Engineering Outstanding New Assistant Professor Award. Tanu received her PhD in Computer Science from Georgia Tech’s School of Interactive Computing and her Masters in Computer Science from Texas A&M University.