We're often told to "be here now." Yet the mind is rarely tethered in place. We take mental trips to our past, revisiting what happened yesterday or when we were children, or we project into an imagined future: tomorrow's dinner date, the trajectory of our career at age 50. Rather than a diversion from the norm of mindful presence, this tendency to internally visit other time lines, called "mental time travel," is common; young adults, for example, think about their future an average of 59 times a day. Psychologists have suggested that this ability to time travel from the confines of our own heads is a fundamental aspect of what it means to be human.

A key challenge in the accurate prediction of viewers' emotional responses to video stimuli in real-world applications is accounting for person- and situation-specific variation. An important contextual influence shaping individuals' subjective experience of a video is the personal memories that it triggers in them. Prior research has found that this memory influence explains more variation in video-induced emotions than other contextual variables commonly used for personalizing predictions, such as viewers' demographics or personality. In this article, we show that (1) automatic analysis of text describing their video-triggered memories can account for variation in viewers' emotional responses, and (2) that combining such an analysis with that of a video's audiovisual content enhances the accuracy of automatic predictions. We discuss the relevance of these findings for improving on state of the art approaches to automated affective video analysis in personalized contexts.