Network visualization and academic storytelling
Network science is a rapidly growing multidisciplinary area that allows us to understand the dynamics of interconnected systems: social, digital, physical, biological, economic, political, and others. This talk will cover ideas related to communicating network research, visualizing network data, and presenting relational information to academic audiences. The discussion will touch on general principles of information visualization, as well as specific ideas related to the visual representation of network structure and properties. The session will also include a few hands-on network visualization examples using R (more detailed R tutorials are available here).
Katherine Ognyanova is an associate professor at the School of Communication & Information, Rutgers University. Her research examines the effects of social influence on civic and political behavior, confidence in institutions, information exposure/evaluation, and public opinion formation. Ognyanova’s methodological expertise is in computational social science, network science, and survey research. Her recent work examines the links between misinformation exposure and political trust. She is also a co-lead on The COVID States Project (covidstates.org) – a large multi-university initiative exploring the social and political implications of COVID-19. You can visit Ognyanova’s website at www.kateto.net or follow her on Twitter at @Ognyanova.
The presentation will be given in English.