Details

Autor(en) / Beteiligte

• Yang, Saelyne
• Yim, Jisu
• Kim, Juho
• Shin, Hijung Valentina
• Barbosa, Simone
• Appert, Caroline
• Lampe, Cliff
• Shamma, David A.
• Yatani, Koji
• Drucker, Steven
• Williamson, Julie

Titel

CatchLive: Real-time Summarization of Live Streams with Stream Content and Interaction Data

Ist Teil von

• Proceedings of the 2022 CHI Conference on Human Factors in Computing Systems, 2022, p.1-20

Ort / Verlag

New York, NY, USA: ACM

Erscheinungsjahr

2022

Link zum Volltext

Quelle

ACM Digital Library【Remote access available】

Beschreibungen/Notizen

• Live streams usually last several hours with many viewers joining in the middle. Viewers who join in the middle often want to understand what has happened in the stream. However, catching up with the earlier parts is challenging because it is difficult to know which parts are important in the long, unedited stream while also keeping up with the ongoing stream. We present CatchLive, a system that provides a real-time summary of ongoing live streams by utilizing both the stream content and user interaction data. CatchLive provides viewers with an overview of the stream along with summaries of highlight moments with multiple levels of detail in a readable format. Results from deployments of three streams with 67 viewers show that CatchLive helps viewers grasp the overview of the stream, identify important moments, and stay engaged. Our findings provide insights into designing summarizations of live streams reflecting their characteristics.