Decoding Reading Goals from Eye Movements
Authors: name: Omer Shubi, name: Cfir Avraham Hadar, name: Yevgeni Berzak

Readers can have different goals with respect to the text they are reading.
Can these goals be decoded from the pattern of their eye movements over the
text? In this work, we examine for the first time whether it is possible to
decode two types of reading goals that are common in daily life: information
seeking and ordinary reading. Using large scale eye-tracking data, we apply to
this task a wide range of state-of-the-art models for eye movements and text
that cover different architectural and data representation strategies, and
further introduce a new model ensemble. We systematically evaluate these models
at three levels of generalization: new textual item, new participant, and the
combination of both. We find that eye movements contain highly valuable signals
for this task. We further perform an error analysis which builds on prior
empirical findings on differences between ordinary reading and information
seeking and leverages rich textual annotations. This analysis reveals key
properties of textual items and participant eye movements that contribute to
the difficulty of the task.