Visual analysis of eye movements during micro-stories reading

Abstract

Reading is a complex task that can provide valuable information about our perceptual and cognitive processes. To understand how people read, researchers have embraced the use of eye-tracking techniques. Recent research work studies the eye movements during reading of short sentences, and however, the extension of these findings to natural reading has not been yet studied in depth. The visual analysis of eye movement data has become an emerging field providing important means to support statistical analysis and hypothesis building. In this work, we focus on the visual analysis of the natural reading of a particular type of text, the micro-stories, which are short-length texts that condense a large amount of information. We present a novel visualization technique for analyzing eye movement data during the reading of micro-stories. In the design of the proposed technique, we consider all the characteristics defined for a typical reading experiment, integrating all of them into a single view. We also provide associated interactions to facilitate exploration. Our novel technique allows the analysis of eye movements during micro-story reading helping the experts to explore relationships among characteristics and to discover hidden relations that help to understand the cognitive process involved.