News Numbers And Public Opinion In A Data Driven World

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.

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.

Science is an essentially cooperative, critical, and dynamic enterprise. Were it not for the continuous creation and improvement of special forms of communication, argumentation, and innovation, all of them suitable for its three key features, scientific knowledge and progress could hardly be achieved. The aim of this volume is to explore the nature of science communication in its several functions, modalities, combinations, and evolution - past, present, and future. One of our objectives is to provide an overview of the richness and variety of elements that take part in performing the complex tasks and fulfilling the functions of science communication. The overall structure and criteria for the choice of topics: 1. The origin and target of a communication episode - its source(s) and addressee(s). 2. The media of communication employed. 3. The thematic field and content types. 4. The distinction between aspects of science communication (e.g., media, texttypes, domains, communicative maxims) and aspects of research on science communication (e.g., the contribution of different research traditions to the understanding of science communication). 5. The history and dynamics of science communication (past, present, and future), both in an empirical perspective (e.g., the development of the research article) and a systematic perspective (e.g., what are basic types and mechanisms of change in science communication).

Do numbers have a life of their own or do we give them meaning? How do data play a role in constructing people's perceptions of the world around them? How far can we trust numbers to speak truth to power? The COVID-19 pandemic offers a unique moment to answer these questions. This book examines how politicians, experts and journalists gave meaning to data through the story of seven iconic numbers from the pandemic.Shedding light on a new dawn of data, this book makes a valuable contribution to our understanding of the relationship between numbers, meaning and society.

An urgent account of the revolution that has upended the news business, written by one of the most accomplished journalists of our time Technology has radically altered the news landscape. Once-powerful newspapers have lost their clout or been purchased by owners with particular agendas. Algorithms select which stories we see. The Internet allows consequential revelations, closely guarded secrets, and dangerous misinformation to spread at the speed of a click. In Breaking News, Alan Rusbridger demonstrates how these decisive shifts have occurred, and what they mean for the future of democracy. In the twenty years he spent editing The Guardian, Rusbridger managed the transformation of the progressive British daily into the most visited serious English-language newspaper site in the world. He oversaw an extraordinary run of world-shaking scoops, including the exposure of phone hacking by London tabloids, the Wikileaks release of U.S.diplomatic cables, and later the revelation of Edward Snowden’s National Security Agency files. At the same time, Rusbridger helped The Guardian become a pioneer in Internet journalism, stressing free access and robust interactions with readers. Here, Rusbridger vividly observes the media’s transformation from close range while also offering a vital assessment of the risks and rewards of practicing journalism in a high-impact, high-stress time.

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.

The starkly different ways that American and French online news companies respond to audience analytics and what this means for the future of news When the news moved online, journalists suddenly learned what their audiences actually liked, through algorithmic technologies that scrutinize web traffic and activity. Has this advent of audience metrics changed journalists’ work practices and professional identities? In Metrics at Work, Angèle Christin documents the ways that journalists grapple with audience data in the form of clicks, and analyzes how new forms of clickbait journalism travel across national borders. Drawing on four years of fieldwork in web newsrooms in the United States and France, including more than one hundred interviews with journalists, Christin reveals many similarities among the media groups examined—their editorial goals, technological tools, and even office furniture. Yet she uncovers crucial and paradoxical differences in how American and French journalists understand audience analytics and how these affect the news produced in each country. American journalists routinely disregard traffic numbers and primarily rely on the opinion of their peers to define journalistic quality. Meanwhile, French journalists fixate on internet traffic and view these numbers as a sign of their resonance in the public sphere. Christin offers cultural and historical explanations for these disparities, arguing that distinct journalistic traditions structure how journalists make sense of digital measurements in the two countries. Contrary to the popular belief that analytics and algorithms are globally homogenizing forces, Metrics at Work shows that computational technologies can have surprisingly divergent ramifications for work and organizations worldwide.

From data-rich infographics to 140 character tweets and activist cell phone photos taken at political protests, 21st century journalism is awash in new ways to report, display, and distribute the news. Computational journalism, in particular, has been the object of recent scholarly and industry attention as large datasets, powerful algorithms, and growing technological capacity at news organizations seemingly empower journalists and editors to report the news in creative ways. Can journalists use data--along with other forms of quantified information such as paper documents of figures, data visualizations, and charts and graphs--in order to produce better journalism? In this book, C.W. Anderson traces the genealogy of data journalism and its material and technological underpinnings, arguing that the use of data in news reporting is inevitably intertwined with national politics, the evolution of computable databases, and the history of professional scientific fields. It is impossible to understand journalistic uses of data, Anderson argues, without understanding the oft-contentious relationship between social science and journalism. It is also impossible to disentangle empirical forms of public truth telling without first understanding the remarkably persistent Progressive belief that the publication of empirically verifiable information will lead to a more just and prosperous world. Anderson considers various types of evidence (documents, interviews, informational graphics, surveys, databases, variables, and algorithms) and the ways these objects have been used through four different eras in American journalism (the Progressive Era, the interpretive journalism movement of the 1930s, the invention of so-called "precision journalism," and today's computational journalistic moment) to pinpoint what counts as empirical knowledge in news reporting. Ultimately the book shows how the changes in these specifically journalistic understandings of evidence can help us think through the current "digital data moment" in ways that go beyond simply journalism.

Bullshit isn’t what it used to be. Now, two science professors give us the tools to dismantle misinformation and think clearly in a world of fake news and bad data. “A modern classic . . . a straight-talking survival guide to the mean streets of a dying democracy and a global pandemic.”—Wired Misinformation, disinformation, and fake news abound and it’s increasingly difficult to know what’s true. Our media environment has become hyperpartisan. Science is conducted by press release. Startup culture elevates bullshit to high art. We are fairly well equipped to spot the sort of old-school bullshit that is based in fancy rhetoric and weasel words, but most of us don’t feel qualified to challenge the avalanche of new-school bullshit presented in the language of math, science, or statistics. In Calling Bullshit, Professors Carl Bergstrom and Jevin West give us a set of powerful tools to cut through the most intimidating data. You don’t need a lot of technical expertise to call out problems with data. Are the numbers or results too good or too dramatic to be true? Is the claim comparing like with like? Is it confirming your personal bias? Drawing on a deep well of expertise in statistics and computational biology, Bergstrom and West exuberantly unpack examples of selection bias and muddled data visualization, distinguish between correlation and causation, and examine the susceptibility of science to modern bullshit. We have always needed people who call bullshit when necessary, whether within a circle of friends, a community of scholars, or the citizenry of a nation. Now that bullshit has evolved, we need to relearn the art of skepticism.

Provides academics, journalists, and general readers with bird's-eye view of data-driven practices and their impact in politics and media.