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Summarizing video content is important for video streaming services to engage the user in a limited time span. To this end, current methods involve manual curation or using passive interest cues to annotate potential high-interest segments to form the basis of summarized videos, and are costly and unreliable. We propose a viewership-driven, automated method that accommodates a range of segment identification goals. Using satellite television viewership data as a source of ground truth forarXiv:2108.04187v1 fatcat:vs6ent5l3jdyfjjxkdlsynkz2y