Analyzing User Engagement with TikTok's Short Format Video Recommendations using Data Donations
arxiv(2023)
摘要
Short-format videos have exploded on platforms like TikTok, Instagram, and
YouTube. Despite this, the research community lacks large-scale empirical
studies into how people engage with short-format videos and the role of
recommendation systems that offer endless streams of such content. In this
work, we analyze user engagement on TikTok using data we collect via a data
donation system that allows TikTok users to donate their data. We recruited 347
TikTok users and collected 9.2M TikTok video recommendations they received. By
analyzing user engagement, we find that the average daily usage time increases
over the users' lifetime while the user attention remains stable at around 45
We also find that users like more videos uploaded by people they follow than
those recommended by people they do not follow. Our study offers valuable
insights into how users engage with short-format videos on TikTok and lessons
learned from designing a data donation system.
更多查看译文
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要