2020/08/27 by Bernd Dudzik, Joost Broekens, Dudzik, Bernd +5
Arts and Humanities · Computer Science · Psychology · #Artificial Intelligence (cs.AI) #Emotion and Mood Recognition #FOS: Computer and information sciences #Human-Computer Interaction (cs.HC) #Media Influence and Health #Mental Health Research Topics #Music and Audio Processing
paper · pdf · doi:10.48550/arxiv.2008.12096
openalex publication_date 2020/08/27 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.