Dylan Walker

Ideology Prediction from Scarce and Biased Supervision: Learn to Disregard the “What” and Focus on the “How”!

We propose a novel supervised learning approach for political ideology prediction (PIP) that is capable of predicting out-of-distribution inputs. This problem is motivated by the fact that manual data-labeling is expensive, while self-reported labels are often scarce and exhibit significant selectio…