Quantifying Political Polarization through the Lens of Machine Translation and Vicarious Offense

This talk surveys three related research contributions that shed light on the current US political divide: 1. a novel machine-translation-based framework to quantify political polarization; 2. an analysis of disparate media portrayal of US policing in major cable news outlets; and 3. a novel perspective of vicarious offense that examines a timely and important question -- how well do Democratic-leaning users perceive what content would be deemed as offensive by their Republican-leaning counterparts or vice-versa?

Authors

• Ashiqur R. KhudaBukhsh Rochester Institute of Technology

Keywords

• Annotation Subjectivity
• News Media Polarization
• Political Polarization
• Vicarious Offense