Examining Multimodal Characteristics of Video to Understand User Engagement

Video content is being produced in ever increasing quantities and offers a potentially highly diverse source for personalizable content. A key characteristic of quality video content is the engaging experience it offers for end users. This paper explores how different characteristics of a video, e.g. face detection, paralinguistic features in the audio track, extracted from different modalities in the video can impact how users rate and thereby engage with the video. These characteristics can further be used to help segment videos in a personalized and contextually aware manner. Initial experimental results from the study presented in this paper provide encouraging results.