Video popularity characterization centered on news-on-demand

Video popularity characterization, in a news-on-demand service, is the core issue of this paper. It will concentrate on the digital edition of six Spanish regional newspapers, where the different news articles are classified into a wide variety of issues. Request video data has been analyzed, including how accesses were distributed along the different topics, during a period of nine months, where the number of requests fluctuated between 85,758 and 586,398 over a minimum of 519 videos and a maximum of 4,221. After an inference and validation process, Box-Cox transformation turned out to be the best choice for the majority of the on-line newspapers. Moreover, the topic related to regional news captured the highest number of requests, so highlighting their regional nature. Finally, new videos achieved 80% of their requests in their first day of life in most of the newspapers, and in four out of six on-line newspapers a high percentage of requests were concentrated on a low percentage of videos (Principle of Pareto).