Documents Healy, Kieran 2 results

"What do markets see when they look at people? Information dragnets increasingly yield huge quantities of individual-level data, which are analyzed to sort and slot people into categories of taste, riskiness or worth. These tools deepen the reach of the market and define new strategies of profit-making. We present a new theoretical framework for understanding their development. We argue that (a) modern organizations follow an institutional data imperative to collect as much data as possible; (b) as a result of the analysis and use of this data, individuals accrue a form of capital flowing from their positions as measured by various digital scoring and ranking methods; and (c) the facticity of these scoring methods makes them organizational devices with potentially stratifying effects. They offer firms new opportunities to structure and price offerings to consumers. For individuals, they create classification situations that identify shared life-chances in product and service markets. We discuss the implications of these processes and argue that they tend toward a new economy of moral judgment, where outcomes are experienced as morally deserved positions based on prior good actions and good tastes, as measured and classified by this new infrastructure of data collection and analysis."

"Through a series of worked examples, the book shows you how to build plots piece by piece, beginning with scatterplots and summaries of single variables, then moving on to more complex graphics. Topics covered include plotting continuous and categorical variables, layering information on graphics; faceting grouped data to produce effective “small multiple” plots; transforming data to easily produce visual summaries on the graph such as trend lines, linear fits, error ranges, and boxplots; creating maps, and also some alternatives to maps worth considering when presenting country- or state-level data. Plotting estimates from statistical models and from complex survey designs are also covered. The book then explores the process of refining plots to accomplish common tasks such as highlighting key features of the data, labeling particular items of interest, annotating plots, and changing their overall appearance. Finally, it discusses some strategies for presenting graphical results in different formats, and to different sorts of audiences.

Learning how to visualize data effectively is more than just knowing how to write code that produces figures from data. This book will teach you how to do that. But it will also teach you how to think about the information you want to show, and how to consider the audience you are showing it to—including the most common case, when the audience is yourself."