Attention Ecology: Trend Circulation And The Virality Threshold

This article demonstrates the use of data mining methodologies for the study and research of social media in the digital humanities. Drawing from recent convergences in writing, rhetoric, and DH research, this article investigates how trends operate within complex networks. Through a study of trend data mined from Twitter, this article suggests the possibility of identifying a virality threshold for Twitter trends, and the possibility that such a threshold has broader implications for attention ecology research in the digital humanities. This article builds on the theories of Jacques Derrida, Richard Lanham, and Sidney Dobrin to suggest new theories and methodologies for understanding how attention operates within complex media ecologies at a macroscopic level. While many various theories and methods have investigated writing, rhetoric, and digital media at the microscopic level, this article contends that a complimentary macroscopic approach is needed to further investigate how attention functions for network culture.