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A key challenge in the accurate prediction of viewers' emotional responses tovideo stimuli in real-world applications is accounting for person- andsituation-specific variation. An important contextual influence shapingindividuals' subjective experience of a video is the personal memories that ittriggers in them. Prior research has found that this memory influence explainsmore variation in video-induced emotions than other contextual variablescommonly used for personalizing predictions, such as viewers' demographics orpersonality. In this article, we show that (1) automatic analysis of textdescribing their video-triggered memories can account for variation in viewers'emotional responses, and (2) that combining such an analysis with that of avideo's audiovisual content enhances the accuracy of automatic predictions. Wediscuss the relevance of these findings for improving on state of the artapproaches to automated affective video analysis in personalized contexts.

A Blast From the Past: Personalizing Predictions of Video-Induced Emotions using Personal Memories as Context