Name
Abstract | ||
|---|---|---|
ABSTRACT As the volume of content and the connectivity of social media have grown, snackable content has increasingly become an enjoyable and engaging way to share content. Snackable content is a shortened form of original content focusing on a single theme or motif for entertainment and quick understanding of a video moment. For content owners with a large library of long-form content (movies, television series, documentaries, etc.), one challenge in accommodating snackable content in social media uses is the correct identification and cutting of interesting regions. Related problems have been studied for algorithmic discovery of content for movie trailers, short-duration meme content, and medium duration news stories, but none of these approaches included user preferences as explicit drivers for cuts. This paper analyzes both human and automatic methods for creating snackable clips across different categories of content with two comprehensive user studies. Contrary to initial expectations, findings amongst the surveyed population indicate a preference for slightly longer snackable clips (60-90 seconds) and those that began or ended with a human character. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1145/3397481.3450690 | IUI |
Keywords | DocType | Citations |
computer vision, user survey, content curation | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Allyson King | 1 | 0 | 0.34 |
| Eric Zavesky | 2 | 0 | 0.34 |
| Michael J. Gonzales | 3 | 0 | 0.34 |