Browsing by Subject "data journalism"

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    Journalism in an Era of Big Data: Cases, Concepts, and Critiques
    (Digital Journalism, 2015) Lewis, Seth C.
    “Journalism in an era of big data” is thus a way of seeing journalism as interpolated through the conceptual and methodological approaches of computation and quantification. It is about both the ideation and implementation of computational and mathematical mindsets and skill sets in newswork—as well as the necessary deconstruction and critique of such approaches. Taking such a wide-angle view of this phenomenon, including both practice and philosophy within this conversation, means attending to the social/cultural dynamics of computation and quantification—such as the grassroots groups that are seeking to bring pro-social “hacking” into journalism (Lewis and Usher 2013, 2014)—as well as the material/technological characteristics of these developments. It means recognizing that algorithms and related computational tools and techniques “are neither entirely material, nor are they entirely human—they are hybrid, composed of both human intentionality and material obduracy” (Anderson 2013, 1016). As such, we need a set of perspectives that highlight the distinct and interrelated roles of social actors and technological actants at this emerging intersection of journalism (Lewis and Westlund 2014a). To trace the broad outline of journalism in an era of big data, we need (1) empirical cases that describe and explain such developments, whether at the micro (local) or macro (institutional) levels of analysis; (2) conceptual frameworks for organizing, interpreting, and ultimately theorizing about such developments; and (3) critical perspectives that call into question taken-for-granted norms and assumptions. This special issue takes up this three-part emphasis on cases, concepts, and critiques.
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    Ways with data: Understanding coding as writing
    (2017-05) Lindgren, Chris
    In this dissertation, I report findings from an exploratory case-study about Ray, a web developer, who works on a data-driven news team that finds and tells compelling stories with large sets of data. I implicate this case of Ray's coding on a data team in a writing studies epistemology, which is guided by the following question: What might be learned about coding, if writing researchers explore the consequences of making language material and computational in a digital medium? I begin this study by outlining a theory of materiality of writing through 6 propositions, which serve as a lens to review literature and theories about coding that articulate the characteristics of code as written communication. From there, I describe my grounded-theory approach to this exploratory case and the battery of ethnographic methods used to collect observational data of Ray's coding over the course of approximately 6 months. Next, I present findings from my grounded analysis across 2 chapters. The first findings chapter cultivates a thick description of Ray, his coding, and how his coding is embedded within a broader objective to find stories in and through aggregate information, which I call aggregate narratives. In the second findings chapter, I conduct a more granular analysis of Ray's coding of goal-oriented slices of data from the original data set source -- a coding practice that produces what I term provisional texts. Findings indicate how Ray's coding of the provisional texts, and the texts themselves, provide active epistemic functions to create aggregate narratives. Finally, I conclude by synthesizing findings with the theoretical propositions about the materialities of writing discussed in the first chapter. Overall, Ray's coding and its materialities show how coding is a dynamic, situated cultural practice, which invites future inquiries into and across domains of coding practices.