Filtering Context Mitigates Scarcity and Selection Bias in Political Ideology Prediction

Chen Chen, Dylan Walker, Venkatesh Saligrama

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 f…