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This volume explores how governments, policymakers and newsrooms have responded to the algorithmic distribution of the news. Contributors analyse the ongoing battle between platforms and publishers, evaluate recent attempts to manage these tensions through policy reform and consider whether algorithms can be regulated to promote media diversity and stop misinformation and hate speech. Chapter authors also interview journalists and find out how their work is changing due to the growing importance of algorithmic systems. Drawing together an international group of scholars, the book takes a truly global perspective offering case studies from Switzerland, Germany, Kenya, New Zealand, Canada, Australia, and China. The collection also provides a series of critical analyses of recent policy developments in the European Union and Australia, which aim to provide a more secure revenue base for news media organisations. A valuable resource for journalism and policy scholars and students, Governing the Algorithmic Distribution of News is an important guide for anyone hoping to understand the central regulatory issues surrounding the online distribution of news.
This book examines the growing importance of algorithms and automation—including emerging forms of artificial intelligence—in the gathering, composition, and distribution of news. In it the authors connect a long line of research on journalism and computation with scholarly and professional terrain yet to be explored. Taken as a whole, these chapters share some of the noble ambitions of the pioneering publications on ‘reporting algorithms’, such as a desire to see computing help journalists in their watchdog role by holding power to account. However, they also go further, firstly by addressing the fuller range of technologies that computational journalism now consists of: from chatbots and recommender systems to artificial intelligence and atomised journalism. Secondly, they advance the literature by demonstrating the increased variety of uses for these technologies, including engaging underserved audiences, selling subscriptions, and recombining and re-using content. Thirdly, they problematise computational journalism by, for example, pointing out some of the challenges inherent in applying artificial intelligence to investigative journalism and in trying to preserve public service values. Fourthly, they offer suggestions for future research and practice, including by presenting a framework for developing democratic news recommenders and another that may help us think about computational journalism in a more integrated, structured manner. The chapters in this book were originally published as a special issue of Digital Journalism.
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.
Scholars from communication and media studies join those from science and technology studies to examine media technologies as complex, sociomaterial phenomena. In recent years, scholarship around media technologies has finally shed the assumption that these technologies are separate from and powerfully determining of social life, looking at them instead as produced by and embedded in distinct social, cultural, and political practices. Communication and media scholars have increasingly taken theoretical perspectives originating in science and technology studies (STS), while some STS scholars interested in information technologies have linked their research to media studies inquiries into the symbolic dimensions of these tools. In this volume, scholars from both fields come together to advance this view of media technologies as complex sociomaterial phenomena. The contributors first address the relationship between materiality and mediation, considering such topics as the lived realities of network infrastructure. The contributors then highlight media technologies as always in motion, held together through the minute, unobserved work of many, including efforts to keep these technologies alive. Contributors Pablo J. Boczkowski, Geoffrey C. Bowker, Finn Brunton, Gabriella Coleman, Gregory J. Downey, Kirsten A. Foot, Tarleton Gillespie, Steven J. Jackson, Christopher M. Kelty, Leah A. Lievrouw, Sonia Livingstone, Ignacio Siles, Jonathan Sterne, Lucy Suchman, Fred Turner
Facebook, a platform created by undergraduates in a Harvard dorm room, has transformed the ways millions of people consume news, understand the world, and participate in the political process. Despite taking on many of journalism’s traditional roles, Facebook and other platforms, such as Twitter and Google, have presented themselves as tech companies—and therefore not subject to the same regulations and ethical codes as conventional media organizations. Challenging such superficial distinctions, Philip M. Napoli offers a timely and persuasive case for understanding and governing social media as news media, with a fundamental obligation to serve the public interest. Social Media and the Public Interest explores how and why social media platforms became so central to news consumption and distribution as they met many of the challenges of finding information—and audiences—online. Napoli illustrates the implications of a system in which coders and engineers drive out journalists and editors as the gatekeepers who determine media content. He argues that a social media–driven news ecosystem represents a case of market failure in what he calls the algorithmic marketplace of ideas. To respond, we need to rethink fundamental elements of media governance based on a revitalized concept of the public interest. A compelling examination of the intersection of social media and journalism, Social Media and the Public Interest offers valuable insights for the democratic governance of today’s most influential shapers of news.
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.
Introduces machine learning and its algorithmic paradigms, explaining the principles behind automated learning approaches and the considerations underlying their usage.
The production and consumption of news in the digital era is blurring the boundaries between professionals, citizens and activists. Actors producing information are multiplying, but still media companies hold central position. Journalism research faces important challenges to capture, examine, and understand the current news environment. The SAGE Handbook of Digital Journalism starts from the pressing need for a thorough and bold debate to redefine the assumptions of research in the changing field of journalism. The 38 chapters, written by a team of global experts, are organised into four key areas: Section A: Changing Contexts Section B: News Practices in the Digital Era Section C: Conceptualizations of Journalism Section D: Research Strategies By addressing both institutional and non-institutional news production and providing ample attention to the question ‘who is a journalist?’ and the changing practices of news audiences in the digital era, this Handbook shapes the field and defines the roadmap for the research challenges that scholars will face in the coming decades.
"As traditional for-profit news media in the United States declines in economic viability and sheer numbers of outlets and staff, what does and what should the constitutional guarantee of freedom of the press mean? The book examines the current news ecosystem in the U.S. and chronicles historical developments in government involvement in shaping the industry. It argues that initiatives by the government and by private-sector actors are not only permitted but called for as transformations in technology, economics, and communications jeopardize the production and distribution of and trust in news and the very existence of local news reporting. It presents ten proposals for change to help preserve the free press essential to our democratic society"--
This book provides in-depth and wide-ranging analyses of the emergence, and subsequent ubiquity, of algorithms in diverse realms of social life. The plurality of Algorithmic Cultures emphasizes: 1) algorithms’ increasing importance in the formation of new epistemic and organizational paradigms; and 2) the multifaceted analyses of algorithms across an increasing number of research fields. The authors in this volume address the complex interrelations between social groups and algorithms in the construction of meaning and social interaction. The contributors highlight the performative dimensions of algorithms by exposing the dynamic processes through which algorithms – themselves the product of a specific approach to the world – frame reality, while at the same time organizing how people think about society. With contributions from leading experts from Media Studies, Social Studies of Science and Technology, Cultural and Media Sociology from Canada, France, Germany, UK and the USA, this volume presents cutting edge empirical and conceptual research that includes case studies on social media platforms, gaming, financial trading and mobile security infrastructures.