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100 Billion Data Rows per Second: Culture Industry and Media Analytics in the Early 21st Century

Forthcoming in International Journal of Communication, special issue “Digital Traces in Context.”

Summary:

Computational analysis of content of digital cultural products and user interactions with this content and with each other is the new stage in the development of modern technological media. It follows the previous stages of massive reproduction (1500-), broadcasting (1920-), automation of media authoring using computers (1981-), use of web for creation of content and distribution (1993-), to name just a few. Since the industry does not have a single term to refer to all practices that characterize this new stage, we can go ahead and coin a name for it. Let’s call it media analytics.

Why do I call this a stage? Because the algorithmic analysis of “cultural data” and "cultural experiences" algorithmic decision-making based on this analysis is not only at work in a few most visible areas such as Google Search and Facebook News. Media analytics practices and technologies are employed in most platforms and services where people share, purchase, and interact with cultural products and with each other. They are used by companies to automatically select what, how, and when will be shown on these platforms to each user, including updates from their friends and recommended content. And perhaps most importantly, they are built into many apps and web services used not only by companies and non-profits but also by millions of individuals who now participate in culture industry not only as consumers but also as content and opinion creators. For example, Google Analytics for websites and blogs, and analytics dashboards provided by Facebook, Twitter and other major social networks are used by millions to fine tune their content and posting strategies.

So far, only one part of media analytics – the practices of gathering and algorithmic analysis of user interaction data - received significant attention. (However, most discussions of this have been only in relation to political and social issues such as privacy, surveillance, access rights, discrimination, fairness, and biases, as opposed to history and theory of technological media.) In contrast, the second key part - the practices of algorithmic analysis of all types of online media content by the industry - received very little attention.

Only if we consider the two parts of media analytics together - analysis of user interaction data and analysis of cultural content – the magnitude of the shift that took place between 1995 and 2010 becomes fully apparent. This is why I am proposing that we should think of media analytics as the new condition of culture industry and also as a new stage in media history. Because its use is now so central to industry as a whole, and because it affects all cultural activities mediated by the web and the apps, we need to start thinking beyond any particular instances and focus more on general principles of media analytics that has already reshaped our cultural lives.

Article  2016