Research Article
Leveraging Big Data Algorithms to Improve Content Quality and User Experience in Large- Scale Video Production
@INPROCEEDINGS{10.4108/eai.23-11-2023.2343191, author={Xiang Li and Anukul Tamprasirt and Fangli Ying}, title={ Leveraging Big Data Algorithms to Improve Content Quality and User Experience in Large- Scale Video Production}, proceedings={Proceedings of the 1st International Conference on Artificial Intelligence, Communication, IoT, Data Engineering and Security, IACIDS 2023, 23-25 November 2023, Lavasa, Pune, India}, publisher={EAI}, proceedings_a={IACIDS}, year={2024}, month={3}, keywords={algorithmic editing content quality user experience conventional editing and likert scale}, doi={10.4108/eai.23-11-2023.2343191} }- Xiang Li
Anukul Tamprasirt
Fangli Ying
Year: 2024
Leveraging Big Data Algorithms to Improve Content Quality and User Experience in Large- Scale Video Production
IACIDS
EAI
DOI: 10.4108/eai.23-11-2023.2343191
Abstract
The explosive growth of video data presents a significant challenge in terms of managing and processing large amounts of visual information in the TV and film production industry. Algorithmic video editing techniques have become crucial in this big data context to efficiently generate informative video content. While many existing works have focused on cost reductions and efficiency improvements, relatively less attention has been paid to user experience and overall video quality. In this study, we conducted a user survey to explore the impact of algorithmic video editing to the user experience and video quality in TV and film production. A total of 110 respondents participated in a 10-point Likert Scale survey to express their views on key dimensions such as content quality, aesthetic appeal, consistency, reliability, information, total waiting time for video production, and likelihood of recommending videos to their friends. The results of the empirical investigation showed that the use of algorithms in editing videos can not only effectively reduce the waiting time but also enhance content quality and user experience in large-scale video production. Participants reported significantly higher satisfaction with algorithmic editing than with raw footage or conventionally edited videos