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.

This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. Such endeavors are making new contributions to the globalization and creating a community of shared future. The 3rd International Conference on Big Data and Social Sciences (ICBDSS 2022) was held on August 19 – 21, 2022, in Hulunbuir, China. With the support of experts and professors, the ICBDSS 2022 conference successfully held its first conference last year. In order to allow more scholars to have the opportunity to participate in the conference to share and exchange experience. This conference mainly focused on "big data", "social science" and other research fields to discuss. At present, my country has entered the era of "big data cloud migration", that is, the era of big data, the Internet of things, cloud computing and mobile Internet. The market demand for big data talents is also increasing day by day. The purpose of the conference is to provide a way for experts, scholars, engineering technicians, and technical R&D personnel engaged in big data and social science research to share scientific research results and cutting-edge technologies, understand academic development trends, broaden research ideas, strengthen academic research and discussion, and promote the academic achievement industry Platform for chemical cooperation. The conference sincerely invites experts, scholars from domestic and foreign universities, scientific research institutions, business people and other relevant personnel to participate in the conference.

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 presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

This is an open access book. As a leading role in the global megatrend of scientific innovation, China has been creating a more and more open environment for scientific innovation, increasing the depth and breadth of academic cooperation, and building a community of innovation that benefits all. These endeavors have made new contribution to globalization and creating a community of shared future. To adapt to this changing world and China's fast development in this new area, the 2nd International Conference on Internet, Education and Information Technology (IEIT 2022) is to be held in April 15-17, 2022. This conference takes “bringing together global wisdom in scientific innovation to promote high-quality development" as the theme and focuses on research fields including information technology, education, big data, and Internet. This conference aims to expand channels of international academic exchange in science and technology, build a sharing platform of academic resources, promote scientific innovation on the global scale, improve academic cooperation between China and the outside world. It also aims to encourage exchange of information on research frontiers in different fields, connect the most advanced academic resources in China and abroad, turn research results into industrial solutions, bring together talents, technologies and capital to boost development.

Winner of the 2019 Robert Picard Book Award The Handbook of Media Management and Economics has become a required reference for students, professors, policy makers and industry practitioners. The volume was developed around two primary objectives: assessing the state of knowledge for the key topics in the media management and economics fields; and establishing the research agenda in these areas, ultimately pushing the field in new directions. The Handbook's chapters are organized into parts addressing the theoretical components, key issues, analytical tools, and future directions for research. With its unparalleled breadth of content from expert authors, the Handbook provides background knowledge of the various theoretical dimensions and historical paradigms, and establishes the direction for the next phases of research in this evolving arena of study. Updates include the rise of mobile and social media, globalization, audience fragmentation and big data.

This book is a theoretical work on data journalism production that drills down the models, narratives, and ethics. From idea to concept and then to a widespread innovative trend, data journalism has become a new global paradigm, facilitating the transformation to focus on data, convergence, and intelligence. Drawing on various theoretical resources of communication, narratology, ethics, management, literature and art, game studies, and data science, this book explores the cutting-edge issues in current data journalism production. It critically analyzes crucial topics, including the boundary generalization of data journalism, data science methodology, the illusion of choice in interactive narratives, the word-image relationship in data visualization, and pragmatic objectivity and transparency in production ethics. Provided with a toolbox of classic examples of global data journalism, this book will be of great value to scholars and students of data journalism or new media, data journalists, and journalism professionals interested in the areas.

Can there be reliable information that is also relevant to decision making? Information for Efficient Decision Making: Big Data, Blockchain and Relevance focuses on the consolidation of information to facilitate making decisions in firms, in order to make their operations efficient to reduce their costs and consequently, increase their profitability. The advent of blockchain has generated great interest as an alternative to centralized organizations, where the data is gathered through a centralized ledger keeping of activities of the firm. The decentralized ledger keeping is one of the main features of blockchain that has given rise to many issues of technology, development, implementation, privacy, acceptance, evaluation and so on. Blockchain concept is a follow-up to big data environment facilitated by enormous progress in computer hardware, storage capacities and technological prowess. This has resulted in the rapid acquiring of data not considered possible earlier. With shrewd modeling analytics and algorithms, the applications have grown to significant levels. This handbook discusses the progress in data collection, pros and cons of collecting information on decentralized publicly available ledgers and several applications.

Technology in the world today impacts every aspect of society and has infiltrated every industry, affecting communication, management, security, etc. With the emergence of such technologies as IoT, big data, cloud computing, AI, and virtual reality, organizations have had to adjust the way they conduct business to account for changing consumer behaviors and increasing data protection awareness. The Handbook of Research on Social and Organizational Dynamics in the Digital Era provides relevant theoretical frameworks and the latest empirical research findings on all aspects of social issues impacted by information technology in organizations and inter-organizational structures and presents the conceptualization of specific social issues and their associated constructs. Featuring coverage on a broad range of topics such as business management, knowledge management, and consumer behavior, this publication seeks to advance the practice and understanding of technology and the impacts of technology on social behaviors and norms in the workplace and society. It is intended for business professionals, executives, IT practitioners, policymakers, students, and researchers.

When technology reinforces inequality, it’s not just a glitch—it’s a signal that we need to redesign our systems to create a more equitable world. The word “glitch” implies an incidental error, as easy to patch up as it is to identify. But what if racism, sexism, and ableism aren’t just bugs in mostly functional machinery—what if they’re coded into the system itself? In the vein of heavy hitters such as Safiya Umoja Noble, Cathy O’Neil, and Ruha Benjamin, Meredith Broussard demonstrates in More Than a Glitch how neutrality in tech is a myth and why algorithms need to be held accountable. Broussard, a data scientist and one of the few Black female researchers in artificial intelligence, masterfully synthesizes concepts from computer science and sociology. She explores a range of examples: from facial recognition technology trained only to recognize lighter skin tones, to mortgage-approval algorithms that encourage discriminatory lending, to the dangerous feedback loops that arise when medical diagnostic algorithms are trained on insufficiently diverse data. Even when such technologies are designed with good intentions, Broussard shows, fallible humans develop programs that can result in devastating consequences. Broussard argues that the solution isn’t to make omnipresent tech more inclusive, but to root out the algorithms that target certain demographics as “other” to begin with. With sweeping implications for fields ranging from jurisprudence to medicine, the ground-breaking insights of More Than a Glitch are essential reading for anyone invested in building a more equitable future.