100 Billion Data Rows per Second: Media Analytics in the Early 21st Century
Publication data: International Journal of Communication 12(2018): 473–488.
This article describes the newest stage in the development of modern technological media. I call this stage “media analytics.” It follows the previous stages of massive reproduction (1500–), broadcasting (1920–), the use of computers for media creation workflows (1981–), the Web as global content creation and distribution network (1993–), and social media platforms (2004–), to name just a few such stages. Unlike other stages, the new stage is not focused on new mechanisms for creation, publishing, or distribution of media, although it also affects these operations. Instead, this new stage is about automatic computational analysis of the content of all online digital media, personal online behaviors and communication, and automatic actions based on this analysis.
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.