From Reading to Pattern Recognition
The emergence of social media creates a radically new opportunity to study cultural processes and dynamics. For the first time, we can follow imagination of hundreds of millions of people – the images and videos they create and comment on, the conversations they are engaged in, the opinions, ideas, and feelings they express.
Until now, the study of the social and the cultural (individual beings, individual artifacts, and larger groups of people/artifacts) relied on two types of data: “shallow data” about many (statistics, sociology) and “deep data” about a few (psychology, psychoanalysis, anthropology, art history; methods such as “thick description” and “close reading”). However, the rise of social media along with the computational tools that can process massive amounts of data makes possible for a fundamentally new approach for the study of human beings and society. We no longer have to choose between data size and data depth. Rather than having to generalize from small samples or rely on our intuition, we can study exact cultural patterns formed by millions of cultural texts. In other words, the detailed knowledge and insights, which before can only be reached about a few texts, can now be obtained about massive collections of these texts.
In 2007, Bruno Latour summarized these developments as follows: “The precise forces that mould our subjectivities and the precise characters that furnish our imaginations are all open to inquiries by the social sciences. It is as if the inner workings of private worlds have been pried open because their inputs and outputs have become thoroughly traceable.” (Bruno Latour, “Beware, your imagination leaves digital traces”, Times Higher Education Literary Supplement, April 6, 2007.)
But how do you “read” through billions of Twitter posts, blogs, Flickr photos, or YouTube videos in practice? That is, how do you read for patterns?