NVISION: Network Visualization Interventions Supporting Interpretation of Objective News
Description
“The current fractured media landscape allows individuals to choose confirming over credible information, and information spreads quicker online than interventions like fact-checking. Misinformation can be debiased by identifying gaps in mental representations of the world (mental models) and prompt alerts to be vigilant about assessing information (Lewandowsky et al, 2012).
We aim to develop interventions to make media-balance salient to users to mitigate the spread of misinformation. Social sampling theory describes that our misperceptions of others is explained by the sample of people we encounter (Galesic, Olsson, and Rieskamp, 2012), and we are more likely to link to similar people online (Kossinets & Watts, 2009). Our interventions address limitations in individual views of the media landscape. We aim to attach visualizations of sharing network to news articles in real-time to make these biases explicit.”
Awards
- Highlighted Project
Students
Advisors
Skills Required by the team
- Data Analysis
- Data Collection
- Data Visualization