Theory-Laden Data Visualization, Drawing-As and Seeing-As in Sociology and in Data Science

Today’s era of ubiquitous big data visualizations begs a return to the philosopher of science’s conceptual territory of theory-laden observation. Using a sociological framework that examines practices of theory-laden representation, I turn to the visual analytics of sociology and data science to elaborate how our everyday data visualizations—regression tables, hashtag clouds, and data dashboards– are also engines of expert theory construal. The resulting visualizations construe qualitative, quantitative, and big data along the lines of expert theoretical, social, and political commitments as they foregound certain aspects and draw other components out of the equation. Bringing seeing-as and drawing-as into the era of big data analytics and computational social science demonstrates how visual analysis betrays theorizing in action, reveals opportunities for epistemic and ontological contestation, and presents novel opportunities to appreciate sociology as a visual science.