2015/05/30 by Cédric Richier, Rachid El-Azouzi, Richier, Cedric +7
Computer Science · Physics and Astronomy · #Caching and Content Delivery #Complex Network Analysis Techniques #FOS: Computer and information sciences #Social and Information Networks (cs.SI) #Spam and Phishing Detection
paper · pdf · doi:10.48550/arxiv.1506.00178
openalex publication_date 2015/05/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper proposes a new prediction process to explain and predict popularity evolution of YouTube videos. We exploit our recent study on the classification of YouTube videos in order to predict the evolution of videos' view-count. This classification allows to identify important factors of the observed popularity dynamics. Our experimental results show that our prediction process is able to reduce the average prediction errors compared to a state-of-the-art baseline model. We also evaluate the impact of adding popularity criteria in our classification.