This book is your guide to understanding what journalism is and could be in an age of digital technology and datafication. Journalism today is entwined with the digital. Stories can come from crowdsourcing and content farms. They can incorporate data visualisations and virtual reality. Journalists can find themselves working as self-employed digital entrepreneurs or for tech giants like Google and Facebook. This book explores the development of journalism in this era of digital tech, and big and open data. It explores the crucial new developments of online journalism, data journalism, computational journalism and entrepreneurial journalism, and what this means for our understanding of journalism as a profession, and as a part of society. Using a wealth of international case studies, Jingrong Tong explores contemporary issues such as: AI, Automated news, ‘robot reporters’, and algorithmic accountability. Digital business models, from venture capital to tech start-ups to crowd-funding. Audiences and dissemination in and age of platform capitalism Questions of censorship, democracy and state control. Digital challenges to journalistic autonomy and legitimacy. With clear explanations throughout, Journalism in the Data Age introduces you to a range of ideas, debates and key concepts. It is essential reading for all students of journalism. Dr Jingrong Tong is Senior Lecturer in Digital News Cultures at the University of Sheffield.
This book is your guide to understanding what journalism is and could be in an age of digital technology and datafication. Journalism today is entwined with the digital. Stories can come from crowdsourcing and content farms. They can incorporate data visualisations and virtual reality. Journalists can find themselves working as self-employed digital entrepreneurs or for tech giants like Google and Facebook. This book explores the development of journalism in this era of digital tech, and big and open data. It explores the crucial new developments of online journalism, data journalism, computational journalism and entrepreneurial journalism, and what this means for our understanding of journalism as a profession, and as a part of society. Using a wealth of international case studies, Jingrong Tong explores contemporary issues such as: AI, Automated news, ‘robot reporters’, and algorithmic accountability. Digital business models, from venture capital to tech start-ups to crowd-funding. Audiences and dissemination in and age of platform capitalism Questions of censorship, democracy and state control. Digital challenges to journalistic autonomy and legitimacy. With clear explanations throughout, Journalism in the Data Age introduces you to a range of ideas, debates and key concepts. It is essential reading for all students of journalism. Dr Jingrong Tong is Senior Lecturer in Digital News Cultures at the University of Sheffield.
Analysing the evolving industry as it turns to the help of digital technologies such as algorithms and cloud computing to reach and engage local and global audiences, Journalism, Economic Uncertainty and Political Irregularity in the Digital and Data Era explores the challenges journalism faces in great depth and detail.
The Brexit referendum on Twitter:a mixed-method computational analysis investigates how Twitter worked in shaping political discourse and its potential for fuelling populism in the month leading to the referendum.
This book maps Twitter discourses on marginalised environmental concerns during the UK’s 2016 EU referendum campaign. Focusing on EU institutional influence in British environmental protection policy and charting the roles played by ENGOs and British political parties, it reveals how British environmental politics extended onto Twitter.
Analysing the evolving industry as it turns to the help of digital technologies such as algorithms and cloud computing to reach and engage local and global audiences, Journalism, Economic Uncertainty and Political Irregularity in the Digital and Data Era explores the challenges journalism faces in great depth and detail.
Considering the interactions between developments in open data and data journalism, Data for Journalism: Between Transparency and Accountability offers an interdisciplinary account of this complex and uncertain relationship in a context of tightening the control over data and weighing transparency against privacy. As data has brought both promise and disruptive changes to societies, the relationship between transparency and accountability has become complicated, and data journalism is practised alongside the contradictory needs of opening up and protecting data. In addition to exploring the benefits of data for journalism, this book addresses the uncertain nature of data and the obstacles preventing data from being fluently accessed and properly used for data reporting. Because of these obstacles, it argues individual data journalists play a decisive role in using data for journalism and facilitating the circulation of data. Frictions in data access, newsrooms’ resources and cultures and data journalists’ skill and data literacy levels determine the degree to which journalism can benefit from data, and these factors potentially exacerbate digital inequalities between newsrooms in different countries and with different resources. As such, the author takes an international perspective, drawing on empirical research and cases from around the world, including countries such as the UK, the US, Germany, Sweden, Australia, India, China and Japan. Introducing a new dimension to the study of developments in journalism and the role of journalism in society, Data for Journalism will be of interest to academics and researchers in the fields of journalism and the sociology of (big and open) data.
Considering the interactions between developments in open data and data journalism, Data for Journalism: Between Transparency and Accountability offers an interdisciplinary account of this complex and uncertain relationship in a context of tightening the control over data and weighing transparency against privacy. As data has brought both promise and disruptive changes to societies, the relationship between transparency and accountability has become complicated, and data journalism is practised alongside the contradictory needs of opening up and protecting data. In addition to exploring the benefits of data for journalism, this book addresses the uncertain nature of data and the obstacles preventing data from being fluently accessed and properly used for data reporting. Because of these obstacles, it argues individual data journalists play a decisive role in using data for journalism and facilitating the circulation of data. Frictions in data access, newsrooms’ resources and cultures and data journalists’ skill and data literacy levels determine the degree to which journalism can benefit from data, and these factors potentially exacerbate digital inequalities between newsrooms in different countries and with different resources. As such, the author takes an international perspective, drawing on empirical research and cases from around the world, including countries such as the UK, the US, Germany, Sweden, Australia, India, China and Japan. Introducing a new dimension to the study of developments in journalism and the role of journalism in society, Data for Journalism will be of interest to academics and researchers in the fields of journalism and the sociology of (big and open) data.
This book examines how the news media in general, and investigative journalism in particular, interprets environmental problems and how those interpretations contribute to the shaping of a discourse of risk that can compete against the omnipresent and hegemonic discourse of modernisation in Chinese society.
The Brexit referendum on Twitter: a mixed method computational analysis investigates how Twitter worked in shaping political discourse and its potential for fuelling populism in the month leading to the referendum.
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