Communicating Data: Data-Driven Storytelling

Abstract

Data is more abundant than ever, yet its utility is diminished by a lack of understanding and difficulty in communicating insights. This thesis seeks to test the effectiveness of data-driven storytelling as a means to solve this disconnect. Research conducted includes reading previous literature on the subject, interviewing journalists and data practitioners as well as learning to use various software tools. This research focuses on communicating engaging stories by finding, cleaning, analyzing and visualizing data using R, Python, Excel, Tableau, Carto and other software tools. The result is a series of data-driven stories published in the Daily Wildcat on a variety of subjects including campus life, politics, and sports. The conclusion of the thesis finds that data-driven storytelling is an effective medium for communicating data and capitalizing on its potential utility. This conclusion is drawn from the fact that humans intuitively understand narrative and data insights parsed out in this familiar form are more easily understood than data presented in an abstract manner.