Automatic document summarization (ADS) has been introduced as a viable solution for reducing the time and the effort needed to read the ever-increasing textual content that is disseminated. However, a successful universal ADS algorithm has not yet been developed. Also, despite progress in the field, many ADS techniques do not take into account the needs of different readers, providing a summary without internal consistency and the consequent need to re-read the original document. The present study was aimed at investigating the usefulness of using eye tracking for increasing the quality of ADS. The general idea was of that of finding ocular behavioural indicators that could be easily implemented in ADS algorithms. For instance, the time spent in re-reading a sentence might reflect the relative importance of that sentence, thus providing a hint for the selection of text contributing to the summary. We have tested this hypothesis by comparing metrics based on the analysis of eye movements of 30 readers with the highlights they made afterward. Results showed that the time spent reading a sentence was not significantly related to its subjective value, thus frustrating our attempt. Results also showed that the length of a sentence is an unavoidable confounding because longer sentences have both the highest probability of containing units of text judged as important, and receive more fixations and re-fixations
