Mining emotions in short films

Short films are regarded as an alternative form of artistic creation, and they express, in a few minutes, a whole gamma of different emotions oriented to impact the audience and communicate a story. In this paper, we exploit a multi-modal sentiment analysis approach to extract emotions in short films, based on the film criticism expressed through social comments from the video-sharing platform YouTube. We go beyond the traditional polarity detection (i.e., positive/negative), and extract, for each analyzed film, four opposing pairs of primary emotions: joy-sadness, anger-fear, trust-disgust, and anticipation-surprise. We found that YouTube comments are a valuable source of information for automatic emotion detection when compared to human analysis elicited via crowdsourcing.