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Dr. Katya Ognyanova & Dr. Lindsay Young present “COVID-19 Information, Misinformation, and Potential Communicative Interventions”
April 13 @ 11:30 am - 1:00 pm CDT
Over the past year the internet, social media, and online messages from friends and family have been central sources of information helping us all navigate the COVID-19 pandemic. In this discussion, two health communication and network science experts will share the challenges and opportunities associated with the increased reliance on online networks as sources of health-related information. Specifically, they will share how misinformation can easily spread online and why the nature of networked digital communication makes it difficult for organizations and institutions to intervene to prevent potentially dangerous messages. The talk will explore ways that patterns of communication may have shifted during the pandemic, the consequences of these changes in communication for efforts to share facts and information to publics, and possible communicative interventions that will help community members make evidence-based decisions.
Dr. Katherine (Katya) Ognyanova is an assistant professor of communication at the Rutgers University School of Communication and Information. She does research in the areas of network science, computational social science, social technology, media, civic, and political communication. Prior to joining Rutgers, she was a postdoctoral research fellow at Northeastern University and Harvard University. Her past experience also includes work with the Annenberg Networks Network, the Center for the Digital Future, the USC Metamorphosis Project, as well as a fellowship with the Federal Communications Commission.
Dr. Lindsay Young is an assistant professor of health communication and communication networks at USC Annenberg. Her research employs social-network and critical perspectives to identify, characterize, and interrogate the social contexts that contribute to and/or facilitate health disparities, access to critical health resources, and health behavior change in marginalized, resource-restricted communities. She has a particular interest in the contextual factors that affect HIV-prevention engagement among young sexual-minority men of color. To these ends, she applies a rich computational toolkit that includes stochastic network modeling, semantic network mapping, computational text analysis and predictive modeling.
Meeting ID: 912 631 2868
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