  We study whether it is possible to infer if a news headline is true or false
using only the movement of the human eyes when reading news headlines. Our
study with 55 participants who are eye-tracked when reading 108 news headlines
(72 true, 36 false) shows that false headlines receive statistically
significantly less visual attention than true headlines. We further build an
ensemble learner that predicts news headline factuality using only eye-tracking
measurements. Our model yields a mean AUC of 0.688 and is better at detecting
false than true headlines. Through a model analysis, we find that eye-tracking
25 users when reading 3-6 headlines is sufficient for our ensemble learner.
