| data science for journalists: The Data Journalism Handbook Jonathan Gray, Lucy Chambers, Liliana Bounegru, 2012-07-12 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 |
| data science for journalists: Computing the News Sylvain Parasie, 2022-10-11 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 science for journalists: Data for Journalists Brant Houston, 2018-12-17 This straightforward and effective how-to guide provides the basics for any reporter or journalism student beginning to use data for news stories. It has step-by-step instructions on how to do basic data analysis in journalism while addressing why these digital tools should be an integral part of reporting in the 21st century. In an ideal core text for courses on data-driven journalism or computer-assisted reporting, Houston emphasizes that journalists are accountable for the accuracy and relevance of the data they acquire and share. With a refreshed design, this updated new edition includes expanded coverage on social media, scraping data from the web, and text-mining, and provides journalists with the tips and tools they need for working with data. |
| data science for journalists: Precision Journalism Philip Meyer, 2002-02-25 Philip Meyer's work in precision journalism established a new and ongoing trend-the use by reporters of social science research techniques to increase the depth and accuracy of major stories. In this fully updated, fourth edition of the classic Precision Journalism (known as The New Precision Journalism in its third edition), Meyer shows journalists and students of journalism how to use new technology to analyze data and provide more precise information in easier-to-understand forms. New to this edition are an overview of the use of theory and science in journalism; game theory applications; introductions to lurking variables and multiple and logistic regression; and developments in election surveys. Key topics retained and updated include elements of data analysis; the use of statistics, computers, surveys, and experiments; database applications; and the politics of precision journalism. This accessible book is an important resource for working journalists and an indispensable text for all journalism majors. |
| data science for journalists: Journalism in an Era of Big Data Seth Lewis, 2018-03-08 Big data is marked by staggering growth in the collection and analysis of digital trace information regarding human and natural activity, bound up in and enabled by the rise of persistent connectivity, networked communication, smart machines, and the internet of things. In addition to their impact on technology and society, these developments have particular significance for the media industry and for journalism as a practice and a profession. These data-centric phenomena are, by some accounts, poised to greatly influence, if not transform, some of the most fundamental aspects of news and its production and distribution by humans and machines. What such changes actually mean for news, democracy, and public life, however, is far from certain. As such, there is a need for scholarly scrutiny and critique of this trend, and this volume thus explores a range of phenomena—from the use of algorithms in the newsroom, to the emergence of automated news stories—at the intersection between journalism and the social, computer, and information sciences. What are the implications of such developments for journalism’s professional norms, routines, and ethics? For its organizations, institutions, and economics? For its authority and expertise? And for the epistemology that underwrites journalism’s role as knowledge-producer and sense-maker in society? Altogether, this book offers a first step in understanding what big data means for journalism. This book was originally published as a special issue of Digital Journalism. |
| data science for journalists: Precision Journalism Philip Meyer, 1979 |
| data science for journalists: The Data Journalism Handbook GRAY, 2021-05-14 This book offers an interdisciplinary introduction to data journalism, offering a unique combination of critical reflection and practical insight into the field, including how data journalism is done around the world and the broader consequences of datafication in the news. |
| data science for journalists: Science Journalism Martin W Angler, 2017-06-14 Science Journalism: An Introduction gives wide-ranging guidance on producing journalistic content about different areas of scientific research. It provides a step-by-step guide to mastering the practical skills necessary for covering scientific stories and explaining the business behind the industry. Martin W. Angler, an experienced science and technology journalist, covers the main stages involved in getting an article written and published; from choosing an idea, structuring your pitch, researching and interviewing, to writing effectively for magazines, newspapers and online publications. There are chapters dedicated to investigative reporting, handling scientific data and explaining scientific practice and research findings to a non-specialist audience. Coverage in the chapters is supported by reading lists, review questions and practical exercises. The book also includes extensive interviews with established science journalists, scholars and scientists that provide tips on building a career in science journalism, address what makes a good reporter and discuss the current issues they face professionally. The book concludes by laying out the numerous available routes into science journalism, such as relevant writing programs, fellowships, awards and successful online science magazines. For students of journalism and professional journalists at all levels, this book offers an invaluable overview of contemporary science journalism with an emphasis on professional journalistic practice and success in the digital age. |
| data science for journalists: Journalism in the Data Age Jingrong Tong, 2022-04-09 A cutting-edge exploration of journalism in the era of digital media technology and big and open data. |
| data science for journalists: Data Feminism Catherine D'Ignazio, Lauren F. Klein, 2020-03-31 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. |
| data science for journalists: Big Data Analytics for Internet of Things Tausifa Jan Saleem, Mohammad Ahsan Chishti, 2021-04-20 BIG DATA ANALYTICS FOR INTERNET OF THINGS Discover the latest developments in IoT Big Data with a new resource from established and emerging leaders in the field Big Data Analytics for Internet of Things delivers a comprehensive overview of all aspects of big data analytics in Internet of Things (IoT) systems. The book includes discussions of the enabling technologies of IoT data analytics, types of IoT data analytics, challenges in IoT data analytics, demand for IoT data analytics, computing platforms, analytical tools, privacy, and security. The distinguished editors have included resources that address key techniques in the analysis of IoT data. The book demonstrates how to select the appropriate techniques to unearth valuable insights from IoT data and offers novel designs for IoT systems. With an abiding focus on practical strategies with concrete applications for data analysts and IoT professionals, Big Data Analytics for Internet of Things also offers readers: A thorough introduction to the Internet of Things, including IoT architectures, enabling technologies, and applications An exploration of the intersection between the Internet of Things and Big Data, including IoT as a source of Big Data, the unique characteristics of IoT data, etc. A discussion of the IoT data analytics, including the data analytical requirements of IoT data and the types of IoT analytics, including predictive, descriptive, and prescriptive analytics A treatment of machine learning techniques for IoT data analytics Perfect for professionals, industry practitioners, and researchers engaged in big data analytics related to IoT systems, Big Data Analytics for Internet of Things will also earn a place in the libraries of IoT designers and manufacturers interested in facilitating the efficient implementation of data analytics strategies. |
| data science for journalists: News, Numbers and Public Opinion in a Data-Driven World An Nguyen, 2017-12-28 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. |
| data science for journalists: Facts are Sacred Simon Rogers, 2013 A full-colour guide to the data that shapes our lives, looking behind the headlines and the soundbites to what's really going on. What are the real effects of the austerity measures? What is the true human cost of the war in Afghanistan? |
| data science for journalists: The Craft of Science Writing Siri Carpenter, 2024-11-05 A deeply sourced, inclusive guide to all aspects of science writing with contributions from some of the most skilled and award-winning authors working today. Science writing has never been so critical to our world, and the demands on writers have never been greater. On any given day, a writer might need to explain the details of AI, analyze developments in climate change research, or serve as a watchdog helping to ensure the integrity of the scientific enterprise. At the same time, writers must spin tales that hook and keep readers, despite the endless other demands on their attention. How does one do it? The Craft of Science Writing is the authoritative guide. With pieces curated from the archives of science writers’ go-to online resource, The Open Notebook, this book explores strategies for finding and shaping story ideas, pitching editors, and building a specialty in science writing. It delves into fundamental skills that every science writer must learn, including planning their reporting; identifying, interviewing, and quoting sources; organizing interview notes; and crafting stories that engage and inform audiences. This expanded edition includes new introductory material and nine new essays focusing on such topics as how to establish a science beat, how to find and use quotes, how to critically evaluate scientific claims, how to use social media for reporting, and how to do data-driven reporting. In addition, there are essays on inclusivity in science writing, offering strategies for eradicating ableist language from stories, working with sensitivity readers, and breaking into English-language media for speakers of other languages. Through interviews with leading journalists offering behind-the-scenes inspiration as well as in-depth essays on the craft offering practical advice, readers will learn how the best science stories get made, from conception to completion. Contributors: Humberto Basilio, Siri Carpenter, Jeanne Erdmann, Dan Ferber, Tina Casagrand Foss, Geoffrey Giller, Laura Helmuth, Jane C. Hu, Alla Katsnelson, Roxanne Khamsi, Betsy Ladyzhets, Jyoti Madhusoodanan, Amanda Mascarelli, Robin Meadows, Kate Morgan, Tiên Nguyễn, Michelle Nijhuis, Aneri Pattani, Rodrigo Pérez Ortega, Mallory Pickett, Kendall Powell, Tasneem Raja, Sandeep Ravindran, Marion Renault, Julia Rosen, Megha Satyanarayana, Christina Selby, Knvul Sheikh, Abdullahi Tsanni, Alexandra Witze, Katherine J. Wu, Wudan Yan, Ed Yong, Rachel Zamzow, Sarah Zhang, and Carl Zimmer |
| data science for journalists: Democracy’s Detectives James Hamilton, 2016-10-10 Winner of the Goldsmith Book Prize, Shorenstein Center on Media, Politics and Public Policy at the Harvard Kennedy School of Government Winner of the Tankard Book Award, Association for Education in Journalism and Mass Communication Winner of the Frank Luther Mott–Kappa Tau Alpha Journalism & Mass Communication Research Award In democratic societies, investigative journalism holds government and private institutions accountable to the public. From firings and resignations to changes in budgets and laws, the impact of this reporting can be significant—but so too are the costs. As newspapers confront shrinking subscriptions and advertising revenue, who is footing the bill for journalists to carry out their essential work? Democracy’s Detectives puts investigative journalism under a magnifying glass to clarify the challenges and opportunities facing news organizations today. “Hamilton’s book presents a thoughtful and detailed case for the indispensability of investigative journalism—and just at the time when we needed it. Now more than ever, reporters can play an essential role as society’s watchdogs, working to expose corruption, greed, and injustice of the years to come. For this reason, Democracy’s Detectives should be taken as both a call to arms and a bracing reminder, for readers and journalists alike, of the importance of the profession.” —Anya Schiffrin, The Nation “A highly original look at exactly what the subtitle promises...Has this topic ever been more important than this year?” —Tyler Cowen, Marginal Revolution |
| data science for journalists: Information Security Essentials Susan E. McGregor, 2021-06-01 As technological and legal changes have hollowed out the protections that reporters and news organizations have depended upon for decades, information security concerns facing journalists as they report, produce, and disseminate the news have only intensified. From source prosecutions to physical attacks and online harassment, the last two decades have seen a dramatic increase in the risks faced by journalists at all levels even as the media industry confronts drastic cutbacks in budgets and staff. As a result, few professional or aspiring journalists have a comprehensive understanding of what is required to keep their sources, stories, colleagues, and reputations safe. This book is an essential guide to protecting news writers, sources, and organizations in the digital era. Susan E. McGregor provides a systematic understanding of the key technical, legal, and conceptual issues that anyone teaching, studying, or practicing journalism should know. Bringing together expert insights from both leading academics and security professionals who work at and with news organizations from BuzzFeed to the Associated Press, she lays out key principles and approaches for building information security into journalistic practice. McGregor draws on firsthand experience as a Wall Street Journal staffer, followed by a decade of researching, testing, and developing information security tools and practices. Filled with practical but evergreen advice that can enhance the security and efficacy of everything from daily beat reporting to long-term investigative projects, Information Security Essentials is a vital tool for journalists at all levels. * Please note that older print versions of this book refer to Reuters' Gina Chua by her previous name. This is being corrected in forthcoming print and digital editions. |
| data science for journalists: Automating the News Nicholas Diakopoulos, 2019-06-10 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. |
| data science for journalists: Advanced Methodologies and Technologies in Media and Communications Mehdi Khosrow-Pour, 2018-08-17 This book provides emerging research on the modern effects of media on cultures, individuals, and groups. While highlighting a range of topics such as social media use and marketing, media influence, and communication technology, this book explores how these advancements shape and further the global society-- |
| data science for journalists: Apostles of Certainty C.W. Anderson, 2018-08-16 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. |
| data science for journalists: The Functional Art Alberto Cairo, 2012-08-22 Unlike any time before in our lives, we have access to vast amounts of free information. With the right tools, we can start to make sense of all this data to see patterns and trends that would otherwise be invisible to us. By transforming numbers into graphical shapes, we allow readers to understand the stories those numbers hide. In this practical introduction to understanding and using information graphics, you’ll learn how to use data visualizations as tools to see beyond lists of numbers and variables and achieve new insights into the complex world around us. Regardless of the kind of data you’re working with–business, science, politics, sports, or even your own personal finances–this book will show you how to use statistical charts, maps, and explanation diagrams to spot the stories in the data and learn new things from it. You’ll also get to peek into the creative process of some of the world’s most talented designers and visual journalists, including Condé Nast Traveler’s John Grimwade , National Geographic Magazine’s Fernando Baptista, The New York Times’ Steve Duenes, The Washington Post’s Hannah Fairfield, Hans Rosling of the Gapminder Foundation, Stanford’s Geoff McGhee, and European superstars Moritz Stefaner, Jan Willem Tulp, Stefanie Posavec, and Gregor Aisch. The book also includes a DVD-ROM containing over 90 minutes of video lessons that expand on core concepts explained within the book and includes even more inspirational information graphics from the world’s leading designers. The first book to offer a broad, hands-on introduction to information graphics and visualization, The Functional Art reveals: • Why data visualization should be thought of as “functional art” rather than fine art • How to use color, type, and other graphic tools to make your information graphics more effective, not just better looking • The science of how our brains perceive and remember information ¿ • Best practices for creating interactive information graphics • A comprehensive look at the creative process behind successful information graphics ¿ • An extensive gallery of inspirational work from the world’s top designers and visual artists On the DVD-ROM: In this introductory video course on information graphics, Alberto Cairo goes into greater detail with even more visual examples of how to create effective information graphics that function as practical tools for aiding perception. You’ll learn how to: incorporate basic design principles in your visualizations, create simple interfaces for interactive graphics, and choose the appropriate type of graphic forms for your data. Cairo also deconstructs successful information graphics from The New York Times and National Geographic magazine with sketches and images not shown in the book. All of Peachpit's eBooks contain the same content as the print edition. You will find a link in the last few pages of your eBook that directs you to the media files. Helpful tips: If you are able to search the book, search for Where are the lesson files? Go to the very last page of the book and scroll backwards. You will need a web-enabled device or computer in order to access the media files that accompany this ebook. Entering the URL supplied into a computer with web access will allow you to get to the files. Depending on your device, it is possible that your display settings will cut off part of the URL. To make sure this is not the case, try reducing your font size and turning your device to a landscape view. This should cause the full URL to appear. |
| data science for journalists: Data Journalism and the Regeneration of News Alfred Hermida, Mary Lynn Young, 2019-02-13 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 journalists: Computer-Assisted Reporting Brant Houston, 2014-11-21 This straightforward and effective how-to guide provides the basics for any journalist or student beginning to use data for news stories. It has step-by-step instructions on how to do basic data analysis in journalism while addressing why these digital tools should be an integral part of reporting in the 21st century. The book pays particular attention to the need for accuracy in computer-assisted reporting and to both the potential and pitfalls in utilizing large datasets in journalism. An ideal core text for courses on data-driven journalism or computer-assisted reporting, Houston pushes back on current trends by helping current and future journalists become more accountable for the accuracy and relevance of the data they acquire and share. Online instructor's materials are available to adopting professors, and additional exercises are available free online to students at the below address: http://ire.org/carbook/ username: carbook password: carbook4 |
| data science for journalists: Introduction to Data Science Laura Igual, Santi Seguí, 2017-02-22 This accessible and classroom-tested textbook/reference presents an introduction to the fundamentals of the emerging and interdisciplinary field of data science. The coverage spans key concepts adopted from statistics and machine learning, useful techniques for graph analysis and parallel programming, and the practical application of data science for such tasks as building recommender systems or performing sentiment analysis. Topics and features: provides numerous practical case studies using real-world data throughout the book; supports understanding through hands-on experience of solving data science problems using Python; describes techniques and tools for statistical analysis, machine learning, graph analysis, and parallel programming; reviews a range of applications of data science, including recommender systems and sentiment analysis of text data; provides supplementary code resources and data at an associated website. |
| data science for journalists: Worlds of Journalism Thomas Hanitzsch, Folker Hanusch, Jyotika Ramaprasad, Arnold S. de Beer, 2019-06-18 How do journalists around the world view their roles and responsibilities in society? Based on a landmark study that has collected data from more than 27,500 journalists in 67 countries, Worlds of Journalism offers a groundbreaking analysis of the different ways journalists perceive their duties, their relationship to society and government, and the nature and meaning of their work. Challenging assumptions of a universal definition or concept of journalism, the book maps a world populated by a rich diversity of journalistic cultures. Organized around a series of key questions on topics such as editorial autonomy, journalistic ethics, trust in social institutions, and changes in the profession, it details how the practice of journalism differs across the world in a range of political, social, and economic contexts. The book covers how journalism as an institution is created and re-created by journalists and how they experience their profession in very different ways, even as they retain a commitment to some basic, widely shared professional norms and practices. It concludes with a global classification of journalistic cultures that reflects the breadth of worldviews and orientations found in disparate countries and regions. Worlds of Journalism offers an ambitious, comparative global understanding of the state of journalism in a time when it is confronting a series of economic and political threats. |
| data science for journalists: Robot Journalism: Can Human Journalism Survive? Noam Lemelshtrich Latar, 2018-03-09 Artificial Intelligence (AI) is changing all aspects of communications and journalism as automatic processes are being introduced into all facets of classical journalism: investigation, content production, and distribution. Traditional human roles in these fields are being replaced by automatic processes and robots.The first section of this book focuses on a discussion of AI, the new emerging field of robot journalism, and the opportunities that AI limitations create for human journalists. The second section offers examples of the new journalism storytelling that empower human journalists using new technologies, new applications, and AI tools. While this book focuses on journalism, the discussion and conclusions are relevant to all content creators, including professionals in the advertising industry, which is a major main source of support for journalism. |
| data science for journalists: Artificial Unintelligence Meredith Broussard, 2019-01-29 A guide to understanding the inner workings and outer limits of technology and why we should never assume that computers always get it right. In Artificial Unintelligence, Meredith Broussard argues that our collective enthusiasm for applying computer technology to every aspect of life has resulted in a tremendous amount of poorly designed systems. We are so eager to do everything digitally—hiring, driving, paying bills, even choosing romantic partners—that we have stopped demanding that our technology actually work. Broussard, a software developer and journalist, reminds us that there are fundamental limits to what we can (and should) do with technology. With this book, she offers a guide to understanding the inner workings and outer limits of technology—and issues a warning that we should never assume that computers always get things right. Making a case against technochauvinism—the belief that technology is always the solution—Broussard argues that it's just not true that social problems would inevitably retreat before a digitally enabled Utopia. To prove her point, she undertakes a series of adventures in computer programming. She goes for an alarming ride in a driverless car, concluding “the cyborg future is not coming any time soon”; uses artificial intelligence to investigate why students can't pass standardized tests; deploys machine learning to predict which passengers survived the Titanic disaster; and attempts to repair the U.S. campaign finance system by building AI software. If we understand the limits of what we can do with technology, Broussard tells us, we can make better choices about what we should do with it to make the world better for everyone. |
| data science for journalists: Journalism Tim P. Vos, 2018-05-22 This volume sets out the state-of-the-art in the discipline of journalism at a time in which the practice and profession of journalism is in serious flux. While journalism is still anchored to its history, change is infecting the field. The profession, and the scholars who study it, are reconceptualizing what journalism is in a time when journalists no longer monopolize the means for spreading the news. Here, journalism is explored as a social practice, as an institution, and as memory. The roles, epistemologies, and ethics of the field are evolving. With this in mind, the volume revisits classic theories of journalism, such as gatekeeping and agenda-setting, but also opens up new avenues of theorizing by broadening the scope of inquiry into an expanded journalism ecology, which now includes citizen journalism, documentaries, and lifestyle journalism, and by tapping the insights of other disciplines, such as geography, economics, and psychology. The volume is a go-to map of the field for students and scholars—highlighting emerging issues, enduring themes, revitalized theories, and fresh conceptualizations of journalism. |
| data science for journalists: Data-Driven Storytelling Nathalie Henry Riche, Christophe Hurter, Nicholas Diakopoulos, Sheelagh Carpendale, 2018-03-28 This book presents an accessible introduction to data-driven storytelling. Resulting from unique discussions between data visualization researchers and data journalists, it offers an integrated definition of the topic, presents vivid examples and patterns for data storytelling, and calls out key challenges and new opportunities for researchers and practitioners. |
| data science for journalists: Verification Handbook Craig Silverman, 2014 |
| data science for journalists: All the News That’s Fit to Click Caitlin Petre, 2021-09-21 From the New York Times to Gawker, a behind-the-scenes look at how performance analytics are transforming journalism today—and how they might remake other professions tomorrow Journalists today are inundated with data about which stories attract the most clicks, likes, comments, and shares. These metrics influence what stories are written, how news is promoted, and even which journalists get hired and fired. Do metrics make journalists more accountable to the public? Or are these data tools the contemporary equivalent of a stopwatch wielded by a factory boss, worsening newsroom working conditions and journalism quality? In All the News That's Fit to Click, Caitlin Petre takes readers behind the scenes at the New York Times, Gawker, and the prominent news analytics company Chartbeat to explore how performance metrics are transforming the work of journalism. Petre describes how digital metrics are a powerful but insidious new form of managerial surveillance and discipline. Real-time analytics tools are designed to win the trust and loyalty of wary journalists by mimicking key features of addictive games, including immersive displays, instant feedback, and constantly updated “scores” and rankings. Many journalists get hooked on metrics—and pressure themselves to work ever harder to boost their numbers. Yet this is not a simple story of managerial domination. Contrary to the typical perception of metrics as inevitably disempowering, Petre shows how some journalists leverage metrics to their advantage, using them to advocate for their professional worth and autonomy. An eye-opening account of data-driven journalism, All the News That's Fit to Click is also an important preview of how the metrics revolution may transform other professions. |
| data science for journalists: Digital Convergence in Contemporary Newsrooms Benedito Medeiros Neto, Inês Amaral, George Ghinea, 2021-11-01 This book explores the dynamic landscape in contemporary newsrooms across three continents by investigating the impact that the processes of searching, processing, and distributing data and information and the use of big data, with secure, automatic, and agile retrieval of information all have in this context. Journalistic organizations have undergone digital transformations, and only those implementing accurate transformations survive. In so doing, the book addresses the fields of e-Communication, Computer Science, and Information Science and other areas of the authors’ expertise. The first five chapters focus on technical visits to investigate newsrooms’ productive routines and flows in major dailies from Brazil, Costa Rica, and England. The remaining chapters consider that the news production routines are cooperative and distributed and at the same time need to be managed from different perspectives to support the convergence of digital media. Last but not least, the book also identifies an increase in ICT-based tools, with an increasing connection from new media combined with the growing trend of digital economy practices as important factors in the new landscape of digital journalism. |
| data science for journalists: The Online Journalism Handbook Paul Bradshaw, Liisa Rohumaa, 2013-09-13 How do we practice journalism in a digital world, in which the old 'rules' no longer apply? This text offers comprehensive, instructive coverage of the techniques and secrets of being a successful online journalist, both from a theoretical and practical point of view. Reflecting the vitality of the web, it will inspire you to acquire new skills and make sense of a transforming industry. Key Features: How to investigate and break stories online Learn to broadcast to millions using video and podcast How to blog like a pro Learn to manage and stimulate user-generated content Include and use social media in your toolkit How to dig out stories using data journalism Rise to the challenge of citizen journalism Make your journalism more interactive at every stage of the process Dedicated chapter for Law and Online Communication The Online Journalism Handbook is essential reading for all journalism students and professionals and of key interest to media, communication studies and more broadly the social sciences. |
| data science for journalists: Digital Journalism, Drones, and Automation Cate Dowd, 2020 The lure of big data and analytics has produced new partnerships between news media and social media and consequently a fragmentation of digital journalism. The era is coupled with the rise in fake news and controversial data sharing. However, creative mobile reporting and civilian drones set new standards for journalist during the European asylum seeker crisis. Yet the focus on data and remote cloud servers continues to dominate online news and journalism, alongside new semantic models for data personalization. News tags that define concepts within a news story to assist search, are now monetized abstractions in accelerated data processing that enables automation and feeds advertising. Can journalism compete with this by defining its own concepts with ethical values named and embedded in algorithms? Can machines make sense of the world in the same way as a traditional journalist? In this book, Cate Dowd analyzes the tasks and ethics of journalists and questions how intelligent machines could simulate ethical human behaviors to better understand the dizzy post-human world of online data. Looking to digital journalism and multi-platform news media, from studios and integrated media systems to mobile reporting in the field, Dowd assesses how data and digital technology has impacted on journalism over the past decade. Dowd's research is informed by in-depth participation with investigative journalists, including images drawn and annotated by industry experts to present key journalism concepts, priorities, and values. Chapters explore approaches for the elicitation of vocabulary for journalism and design methods to embed values and ethics into algorithms for the era of automation and big data. Digital Journalism, Drones, and Automation provides insights into the lasting values of journalism processes and equips readers interested in entering or understanding online data and news media with much needed context and wisdom. |
| data science for journalists: Networking Peripheries Anita Say Chan, 2024-05-21 An exploration of the diverse experiments in digital futures as they advance far from the celebrated centers of technological innovation and entrepreneurship. In Networking Peripheries, Anita Chan shows how digital cultures flourish beyond Silicon Valley and other celebrated centers of technological innovation and entrepreneurship. The evolving digital cultures in the Global South vividly demonstrate that there are more ways than one to imagine what digital practice and global connection could look like. To explore these alternative developments, Chan investigates the diverse initiatives being undertaken to “network” the nation in contemporary Peru, from attempts to promote the intellectual property of indigenous artisans to the national distribution of digital education technologies to open technology activism in rural and urban zones. Drawing on ethnographic accounts from government planners, regional free-software advocates, traditional artisans, rural educators, and others, Chan demonstrates how such developments unsettle dominant conceptions of information classes and innovations zones. Government efforts to turn rural artisans into a new creative class progress alongside technology activists' efforts to promote indigenous rights through information tactics; plans pressing for the state wide adoption of open source–based technologies advance while the One Laptop Per Child initiative aims to network rural classrooms by distributing laptops. As these cases show, the digital cultures and network politics emerging on the periphery do more than replicate the technological future imagined as universal from the center. |
| data science for journalists: Data Science for Undergraduates National Academies of Sciences, Engineering, and Medicine, Division of Behavioral and Social Sciences and Education, Board on Science Education, Division on Engineering and Physical Sciences, Committee on Applied and Theoretical Statistics, Board on Mathematical Sciences and Analytics, Computer Science and Telecommunications Board, Committee on Envisioning the Data Science Discipline: The Undergraduate Perspective, 2018-11-11 Data science is emerging as a field that is revolutionizing science and industries alike. Work across nearly all domains is becoming more data driven, affecting both the jobs that are available and the skills that are required. As more data and ways of analyzing them become available, more aspects of the economy, society, and daily life will become dependent on data. It is imperative that educators, administrators, and students begin today to consider how to best prepare for and keep pace with this data-driven era of tomorrow. Undergraduate teaching, in particular, offers a critical link in offering more data science exposure to students and expanding the supply of data science talent. Data Science for Undergraduates: Opportunities and Options offers a vision for the emerging discipline of data science at the undergraduate level. This report outlines some considerations and approaches for academic institutions and others in the broader data science communities to help guide the ongoing transformation of this field. |
| data science for journalists: Newsmakers Francesco Marconi, 2020-04-07 Will the use of artificial intelligence (AI), algorithms, and smart machines be the end of journalism as we know it—or its savior? In Newsmakers, Francesco Marconi, who has led the development of the Associated Press and Wall Street Journal’s use of AI in journalism, offers a new perspective on the potential of these technologies. He explains how reporters, editors, and newsrooms of all sizes can take advantage of the possibilities they provide to develop new ways of telling stories and connecting with readers. Marconi analyzes the challenges and opportunities of AI through case studies ranging from financial publications using algorithms to write earnings reports to investigative reporters analyzing large data sets to outlets determining the distribution of news on social media. Newsmakers contends that AI can augment—not automate—the industry, allowing journalists to break more news more quickly while simultaneously freeing up their time for deeper analysis. Marshaling insights drawn from firsthand experience, Marconi maps a media landscape transformed by artificial intelligence for the better. In addition to considering the benefits of these new technologies, Marconi stresses the continuing need for editorial and institutional oversight. Newsmakers outlines the important questions that journalists and media organizations should consider when integrating AI and algorithms into their workflow. For journalism students as well as seasoned media professionals, Marconi’s insights provide much-needed clarity and a practical roadmap for how AI can best serve journalism. |
| data science for journalists: Software Literacy Elaine Khoo, Craig Hight, Rob Torrens, Bronwen Cowie, 2017-11-24 This book explores the notion of software literacy, a key part of digital literacy which all contemporary students and citizens need to understand. Software literacy involves a critical understanding of how the affordances and conceptual approaches of everything from operating systems, creative apps and media editors, to software-based platforms and infrastructures work to inform and shape the ways we think and act. As a cultural artefact, programing code plays a role in reproducing, reinforcing, and augmenting existing cultural practices, as well as generating completely new coded practices. A proposed three-tier framework for software literacy is the focus for a two-year empirical investigation into how tertiary students become more literate about the nature and implications of software they encounter as part of their tertiary studies. Two case studies of software learning and use in university-level engineering and screen & media studies courses are presented, investigating the mapping of students’ trajectory of the learning of desktop applications against this framework for software literacy. Though the book’s focus is primarily educational, its content also has implications for any field that makes use of software and information & communication technology systems and applications. As such, the book will be of interest to all readers whose work involves the challenges and opportunities presented by software-based teaching and learning; and to those interested in how software impacts the workplace and leisure activities that make up our day-to-day lives. |
| data science for journalists: The Truthful Art Alberto Cairo, 2016-02-08 No matter what your actual job title, you are—or soon will be—a data worker. Every day, at work, home, and school, we are bombarded with vast amounts of free data collected and shared by everyone and everything from our co-workers to our calorie counters. In this highly anticipated follow-up to The Functional Art—Alberto Cairo’s foundational guide to understanding information graphics and visualization—the respected data visualization professor explains in clear terms how to work with data, discover the stories hidden within, and share those stories with the world in the form of charts, maps, and infographics. In The Truthful Art, Cairo transforms elementary principles of data and scientific reasoning into tools that you can use in daily life to interpret data sets and extract stories from them. The Truthful Art explains: • The role infographics and data visualization play in our world • Basic principles of data and scientific reasoning that anyone can master • How to become a better critical thinker • Step-by-step processes that will help you evaluate any data visualization (including your own) • How to create and use effective charts, graphs, and data maps to explain data to any audience The Truthful Art is also packed with inspirational and educational real-world examples of data visualizations from such leading publications as The New York Times, The Wall Street Journal, Estado de São Paulo (Brazil), Berliner Morgenpost (Germany), and many more. |
| data science for journalists: Mining Social Media Lam Thuy Vo, 2019-11-25 BuzzFeed News Senior Reporter Lam Thuy Vo explains how to mine, process, and analyze data from the social web in meaningful ways with the Python programming language. Did fake Twitter accounts help sway a presidential election? What can Facebook and Reddit archives tell us about human behavior? In Mining Social Media, senior BuzzFeed reporter Lam Thuy Vo shows you how to use Python and key data analysis tools to find the stories buried in social media. Whether you're a professional journalist, an academic researcher, or a citizen investigator, you'll learn how to use technical tools to collect and analyze data from social media sources to build compelling, data-driven stories. Learn how to: Write Python scripts and use APIs to gather data from the social web Download data archives and dig through them for insights Inspect HTML downloaded from websites for useful content Format, aggregate, sort, and filter your collected data using Google Sheets Create data visualizations to illustrate your discoveries Perform advanced data analysis using Python, Jupyter Notebooks, and the pandas library Apply what you've learned to research topics on your own Social media is filled with thousands of hidden stories just waiting to be told. Learn to use the data-sleuthing tools that professionals use to write your own data-driven stories. |
| data science for journalists: Metrics at Work Angèle Christin, 2020-06-30 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. |
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use and open science. This will …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open data by default, and made available with …
Belmont Forum Adopts Open Data Principles for Environmental …
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data Management for Global Change Research, …
Belmont Forum Data Accessibility Statement and Policy
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. Access to data promotes reproducibility, …
Climate-Induced Migration in Africa and Beyond: Big Data and …
CLIMB will also leverage earth observation and social media data, and combine them with survey and official statistical data. This holistic approach will allow us to analyze migration process …
Advancing Resilience in Low Income Housing Using Climate …
Jun 4, 2020 · Environmental sustainability and public health considerations will be included. Machine Learning and Big Data Analytics will be used to identify optimal disaster resilient …
Belmont Forum
What is the Belmont Forum? The Belmont Forum is an international partnership that mobilizes funding of environmental change research and accelerates its delivery to remove critical …
Waterproofing Data: Engaging Stakeholders in Sustainable Flood …
Apr 26, 2018 · Waterproofing Data investigates the governance of water-related risks, with a focus on social and cultural aspects of data practices. Typically, data flows up from local levels …
Data Management Annex (Version 1.4) - Belmont Forum
A full Data Management Plan (DMP) for an awarded Belmont Forum CRA project is a living, actively updated document that describes the data management life cycle for the data to be …
Data and Digital Outputs Management Plan (DDOMP)
Data and Digital Outputs Management Plan (DDOMP)
Building New Tools for Data Sharing and Reuse through a …
Jan 10, 2019 · The SEI CRA will closely link research thinking and technological innovation toward accelerating the full path of discovery-driven data use …
Open Data Policy and Principles - Belmont Forum
The data policy includes the following principles: Data should be: Discoverable through catalogues and search engines; Accessible as open …
Belmont Forum Adopts Open Data Principles for Environme…
Jan 27, 2016 · Adoption of the open data policy and principles is one of five recommendations in A Place to Stand: e-Infrastructures and Data …
Belmont Forum Data Accessibility Statement an…
The DAS encourages researchers to plan for the longevity, reusability, and stability of the data attached to their research publications and results. …
