Netflix: content catalog and television flow in times of big data - Heredia-Ruiz, Verónica (2021)
This article aims to identify the way in which the Netflix platform demonstrates the concept of television flow in its catalog, based on the analysis of the original content of fiction series released in 2019. It also recognizes some programming strategies and techniques that implements this video streaming platform, considering the implications of big data and recommendation systems. The methodology contemplates qualitative and quantitative techniques and applies an analysis matrix based on a manual coding of 157 original fiction series, with variables such as launch date, origin of production, season number, chapters and total minutes released per season. Among the main findings, it is evident that Netflix achieves a television flow with permanent premieres throughout the year, the launch of content by seasons with full chapters, as well as the election of Friday and the spring season for the launch of a greater number of fiction productions. It was also found that, although this streaming service seeks a diversification of the catalog with productions from different countries, the original serial fiction content continues to be mainly of American origin. It is concluded that the programming dynamics in the Netflix catalog creates a television flow to promote intensive consumption in the premieres of original fiction series. The catalog is optimized through data-based decisions and promotes viewing with content recommendation systems that allow the creation of an entire Netflix experience.