Computing the News
Computing the News

Author: Sylvain Parasie

Publisher: Columbia University Press

Published: 2022-10-11

Total Pages: 169

ISBN-13: 0231553277

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Faced with a full-blown crisis, a growing number of journalists are engaging in seemingly unjournalistic practices such as creating and maintaining databases, handling algorithms, or designing online applications. “Data journalists” claim that these approaches help the profession demonstrate greater objectivity and fulfill its democratic mission. In their view, computational methods enable journalists to better inform their readers, more closely monitor those in power, and offer deeper analysis. In Computing the News, Sylvain Parasie examines how data journalists and news organizations have navigated the tensions between traditional journalistic values and new technologies. He traces the history of journalistic hopes for computing technology and contextualizes the surge of data journalism in the twenty-first century. By importing computational techniques and ways of knowing new to journalism, news organizations have come to depend on a broader array of human and nonhuman actors. Parasie draws on extensive fieldwork in the United States and France, including interviews with journalists and data scientists as well as a behind-the-scenes look at several acclaimed projects in both countries. Ultimately, he argues, fulfilling the promise of data journalism requires the renewal of journalistic standards and ethics. Offering an in-depth analysis of how computing has become part of the daily practices of journalists, this book proposes ways for journalism to evolve in order to serve democratic societies.

Data Journalism and the Regeneration of News
Data Journalism and the Regeneration of News

Author: Alfred Hermida

Publisher: Routledge

Published: 2019-02-13

Total Pages: 165

ISBN-13: 1351672509

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Data Journalism and the Regeneration of News traces the emergence of data journalism through a scholarly lens. It reveals the growth of data journalism as a subspecialty, cultivated and sustained by an increasing number of professional identities, tools and technologies, educational opportunities and new forms of collaboration and computational thinking. The authors base their analysis on five years of in-depth field research, largely in Canada, an example of a mature media system. The book identifies how data journalism’s development is partly due to it being at the center of multiple crises and shocks to journalism, including digitalization, acute mis- and dis-information concerns and increasingly participatory audiences. It highlights how data journalists, particularly in well-resourced newsrooms, are able to address issues of trust and credibility to advance their professional interests. These journalists are operating as institutional entrepreneurs in a field still responding to the disruption effects of digitalization more than 20 years ago. By exploring the ways in which data journalists are strategically working to modernize the way journalists talk about methods and maintain journalism authority, Data Journalism and the Regeneration of News introduces an important new dimension to the study of digital journalism for researchers, students and educators.

Data Science for Fake News
Data Science for Fake News

Author: Deepak P

Publisher: Springer Nature

Published: 2021-04-29

Total Pages: 302

ISBN-13: 3030626962

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This book provides an overview of fake news detection, both through a variety of tutorial-style survey articles that capture advancements in the field from various facets and in a somewhat unique direction through expert perspectives from various disciplines. The approach is based on the idea that advancing the frontier on data science approaches for fake news is an interdisciplinary effort, and that perspectives from domain experts are crucial to shape the next generation of methods and tools. The fake news challenge cuts across a number of data science subfields such as graph analytics, mining of spatio-temporal data, information retrieval, natural language processing, computer vision and image processing, to name a few. This book will present a number of tutorial-style surveys that summarize a range of recent work in the field. In a unique feature, this book includes perspective notes from experts in disciplines such as linguistics, anthropology, medicine and politics that will help to shape the next generation of data science research in fake news. The main target groups of this book are academic and industrial researchers working in the area of data science, and with interests in devising and applying data science technologies for fake news detection. For young researchers such as PhD students, a review of data science work on fake news is provided, equipping them with enough know-how to start engaging in research within the area. For experienced researchers, the detailed descriptions of approaches will enable them to take seasoned choices in identifying promising directions for future research.

Child Data Citizen
Child Data Citizen

Author: Veronica Barassi

Publisher: MIT Press

Published: 2020-12-22

Total Pages: 233

ISBN-13: 0262044714

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An examination of the datafication of family life--in particular, the construction of our children into data subjects. Our families are being turned into data, as the digital traces we leave are shared, sold, and commodified. Children are datafied even before birth, with pregnancy apps and social media postings, and then tracked through babyhood with learning apps, smart home devices, and medical records. If we want to understand the emergence of the datafied citizen, Veronica Barassi argues, we should look at the first generation of datafied natives: our children. In Child Data Citizen, she examines the construction of children into data subjects, describing how their personal information is collected, archived, sold, and aggregated into unique profiles that can follow them across a lifetime.

The Data Journalism Handbook
The Data Journalism Handbook

Author: Jonathan Gray

Publisher: "O'Reilly Media, Inc."

Published: 2012-07-12

Total Pages: 243

ISBN-13: 1449330029

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When you combine the sheer scale and range of digital information now available with a journalist’s "nose for news" and her ability to tell a compelling story, a new world of possibility opens up. With The Data Journalism Handbook, you’ll explore the potential, limits, and applied uses of this new and fascinating field. This valuable handbook has attracted scores of contributors since the European Journalism Centre and the Open Knowledge Foundation launched the project at MozFest 2011. Through a collection of tips and techniques from leading journalists, professors, software developers, and data analysts, you’ll learn how data can be either the source of data journalism or a tool with which the story is told—or both. Examine the use of data journalism at the BBC, the Chicago Tribune, the Guardian, and other news organizations Explore in-depth case studies on elections, riots, school performance, and corruption Learn how to find data from the Web, through freedom of information laws, and by "crowd sourcing" Extract information from raw data with tips for working with numbers and statistics and using data visualization Deliver data through infographics, news apps, open data platforms, and download links

The Infographic
The Infographic

Author: Murray Dick

Publisher: MIT Press

Published: 2020-04-21

Total Pages: 243

ISBN-13: 0262043823

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An exploration of infographics and data visualization as a cultural phenomenon, from eighteenth-century print culture to today's data journalism. Infographics and data visualization are ubiquitous in our everyday media diet, particularly in news—in print newspapers, on television news, and online. It has been argued that infographics are changing what it means to be literate in the twenty-first century—and even that they harmonize uniquely with human cognition. In this first serious exploration of the subject, Murray Dick traces the cultural evolution of the infographic, examining its use in news—and resistance to its use—from eighteenth-century print culture to today's data journalism. He identifies six historical phases of infographics in popular culture: the proto-infographic, the classical, the improving, the commercial, the ideological, and the professional. Dick describes the emergence of infographic forms within a wider history of journalism, culture, and communications, focusing his analysis on the UK. He considers their use in the partisan British journalism of late eighteenth and early nineteenth-century print media; their later deployment as a vehicle for reform and improvement; their mass-market debut in the twentieth century as a means of explanation (and sometimes propaganda); and their use for both ideological and professional purposes in the post–World War II marketized newspaper culture. Finally, he proposes best practices for news infographics and defends infographics and data visualization against a range of criticism. Dick offers not only a history of how the public has experienced and understood the infographic, but also an account of what data visualization can tell us about the past.

Dear Data
Dear Data

Author: Giorgia Lupi

Publisher: Chronicle Books

Published: 2016-09-13

Total Pages: 304

ISBN-13: 1616895462

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Equal parts mail art, data visualization, and affectionate correspondence, Dear Data celebrates "the infinitesimal, incomplete, imperfect, yet exquisitely human details of life," in the words of Maria Popova (Brain Pickings), who introduces this charming and graphically powerful book. For one year, Giorgia Lupi, an Italian living in New York, and Stefanie Posavec, an American in London, mapped the particulars of their daily lives as a series of hand-drawn postcards they exchanged via mail weekly—small portraits as full of emotion as they are data, both mundane and magical. Dear Data reproduces in pinpoint detail the full year's set of cards, front and back, providing a remarkable portrait of two artists connected by their attention to the details of their lives—including complaints, distractions, phone addictions, physical contact, and desires. These details illuminate the lives of two remarkable young women and also inspire us to map our own lives, including specific suggestions on what data to draw and how. A captivating and unique book for designers, artists, correspondents, friends, and lovers everywhere.

Data Feminism
Data Feminism

Author: Catherine D'Ignazio

Publisher: MIT Press

Published: 2020-03-31

Total Pages: 328

ISBN-13: 0262358530

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A new way of thinking about data science and data ethics that is informed by the ideas of intersectional feminism. Today, data science is a form of power. It has been used to expose injustice, improve health outcomes, and topple governments. But it has also been used to discriminate, police, and surveil. This potential for good, on the one hand, and harm, on the other, makes it essential to ask: Data science by whom? Data science for whom? Data science with whose interests in mind? The narratives around big data and data science are overwhelmingly white, male, and techno-heroic. In Data Feminism, Catherine D'Ignazio and Lauren Klein present a new way of thinking about data science and data ethics—one that is informed by intersectional feminist thought. Illustrating data feminism in action, D'Ignazio and Klein show how challenges to the male/female binary can help challenge other hierarchical (and empirically wrong) classification systems. They explain how, for example, an understanding of emotion can expand our ideas about effective data visualization, and how the concept of invisible labor can expose the significant human efforts required by our automated systems. And they show why the data never, ever “speak for themselves.” Data Feminism offers strategies for data scientists seeking to learn how feminism can help them work toward justice, and for feminists who want to focus their efforts on the growing field of data science. But Data Feminism is about much more than gender. It is about power, about who has it and who doesn't, and about how those differentials of power can be challenged and changed.

News, Numbers and Public Opinion in a Data-Driven World
News, Numbers and Public Opinion in a Data-Driven World

Author: An Nguyen

Publisher: Bloomsbury Publishing USA

Published: 2017-12-28

Total Pages: 305

ISBN-13: 1501330357

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From the quality of the air we breathe to the national leaders we choose, data and statistics are a pervasive feature of daily life and daily news. But how do news, numbers and public opinion interact with each other ? and with what impacts on society at large? Featuring an international roster of established and emerging scholars, this book is the first comprehensive collection of research into the little understood processes underpinning the uses/misuses of statistical information in journalism and their socio-psychological and political effects. Moving beyond the hype around ?data journalism," News, Numbers and Public Opinion delves into a range of more latent, fundamental questions such as: � Is it true that most citizens and journalists do not have the necessary skills and resources to critically process and assess numbers? � How do/should journalists make sense of the increasingly data-driven world? � What strategies, formats and frames do journalists use to gather and represent different types of statistical data in their stories? � What are the socio-psychological and political effects of such data gathering and representation routines, formats and frames on the way people acquire knowledge and form attitudes? � What skills and resources do journalists and publics need to deal effectively with the influx of numbers into in daily work and life ? and how can newsrooms and journalism schools meet that need? The book is a must-read for not only journalists, journalism and media scholars, statisticians and data scientists but also anybody interested in the interplay between journalism, statistics and society.

Automating the News
Automating the News

Author: Nicholas Diakopoulos

Publisher: Harvard University Press

Published: 2019-06-10

Total Pages: 337

ISBN-13: 0674239318

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From hidden connections in big data to bots spreading fake news, journalism is increasingly computer-generated. An expert in computer science and media explains the present and future of a world in which news is created by algorithm. Amid the push for self-driving cars and the roboticization of industrial economies, automation has proven one of the biggest news stories of our time. Yet the wide-scale automation of the news itself has largely escaped attention. In this lively exposé of that rapidly shifting terrain, Nicholas Diakopoulos focuses on the people who tell the stories—increasingly with the help of computer algorithms that are fundamentally changing the creation, dissemination, and reception of the news. Diakopoulos reveals how machine learning and data mining have transformed investigative journalism. Newsbots converse with social media audiences, distributing stories and receiving feedback. Online media has become a platform for A/B testing of content, helping journalists to better understand what moves audiences. Algorithms can even draft certain kinds of stories. These techniques enable media organizations to take advantage of experiments and economies of scale, enhancing the sustainability of the fourth estate. But they also place pressure on editorial decision-making, because they allow journalists to produce more stories, sometimes better ones, but rarely both. Automating the News responds to hype and fears surrounding journalistic algorithms by exploring the human influence embedded in automation. Though the effects of automation are deep, Diakopoulos shows that journalists are at little risk of being displaced. With algorithms at their fingertips, they may work differently and tell different stories than they otherwise would, but their values remain the driving force behind the news. The human–algorithm hybrid thus emerges as the latest embodiment of an age-old tension between commercial imperatives and journalistic principles.