| Summary: | Online videos have become the most popular method to obtain information for the public in recent years, such as TikTok and YouTube, and regional sites like Bilibili and Douyin. Compared with its growing influence, the analysis of user behavior on video sites is still less investigated. Herein, we fetch the video data from Bilibili.com and analyze the video views, comments, and other behaviors on the website. We found that the description model based on the Hawkes process can accurately predict the video views, which suggests that on the Bilibili website, the self-incentive mechanism of information cascade diffusion plays a decisive role in online views. Meanwhile, we also found that the view increment of the videos during the same period of time conforms to the general power-law distribution.
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