CE38 - Révolution numérique : rapports au savoir et à la culture

Between Complex Networks and Market: YouTube from a Computational Social Sciences Perspective – APY

Submission summary

As new communication space, YouTube brings together millions of users around the world and has generated considerable economic activity. How much do creators earn on YouTube? How is the value shared? Is this platform more a commercial space or a sharing economy? APY project''s main objective is to answer these questions by analyzing YouTube through a socio-economics of content. The platform is tought of as a market with various socio-economic models: if entry costs are null, popularity is hard to build. Channels adopt financing strategies according to their own characteristics, their specialty themes, the shape of their fan, brand and collaborator networks and the support of the recommendation system. These strategies developed in the construction of their interest which in return influences the possible modes of financing.

APY proposes here to articulate the techniques of computational sciences and the interpretative frameworks of sociology and economics. From a material of great wealth, APY relies on an original partnership between a part of researchers in social and computer sciences and on the other hand, a company, Wizdeo, specialized in YouTube Metrics, a multi-channel-network (MCN). The project presents a unique opportunity: that of analyzing a corpus of channels operating on different segments of the French market, as well as the characteristics of the different networks which underlie them, the origins of the video views and the earnings reported by the channels.

The analysis of this corpus of 40,000 channels will allow us to deepen our knowledge of YouTube, the place of digital convergence of the cultural and media industries. Our premise is that the YouTube economy is based on maintaining a tension between mercantile contract and social contract. Thus, we analyze the functioning of the YouTube market from many source of revenue ( advertising, sponsoring crowdfunding (objective 1); we are exploring the impacts of the various networks which link channels and content, in particular the role of the recommendation system on visibility, and therefore the income of creators (objective 2); we will rethink the socio-economic models of the content industries active on YouTube and their effects on product diversification (objective 3); we will produce metadata of actors, actions and genres from the content of the videos (objective 4); Finally, we will co-build models for Wizdeo, fully meeting the objective of researcher / company collaboration, at the heart of this call for projects (objective 5).

To do this, this project must be able to take advantage of technological barriers, at the level of the collection and processing of massive data, so far little or not exploited, then at a theoretical level of implementation of new socio-economic models.

The scientific results presented within the framework of the project are twofold: one part, it is impossible to distribute the methodology of computing sciences through new methods of computing networks and the development of an adaptive learning system for video categories ; on the other hand, on a theoretical level, it will make it possible to test new comprehensive socio-economic models of the media and culture industry markets on YouTube. The expected industrial benefit of the project is directly linked to the use of this new knowledge to integrate the metrics in the Wizdeo Analytics tool, in particular income prediction metrics. APY also appears as a research of general interest by accompanying the public actors, in particular the Superior council of Audiovisual (CSA), in the analysis of the operation and the effects of the platform on the distribution of the contents.

Project coordination

Bilel BENBOUZID (Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés)

The author of this summary is the project coordinator, who is responsible for the content of this summary. The ANR declines any responsibility as for its contents.

Partner

LIGM Laboratoire d'Informatique Gaspard-Monge
LISIS Laboratoire Interdisciplinaire Sciences, Innovations, Sociétés
WIZDEO
LTCI Laboratoire Traitement et Communication de l'Information

Help of the ANR 553,205 euros
Beginning and duration of the scientific project: December 2020 - 48 Months

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