In this book, Xiaoqun Zhang argues that acquiring knowledge of machine learning (ML) and artificial intelligence (AI) tools is increasingly imperative for the trajectory of communication research in the era of big data. Rather than simply being a matter of keeping pace with technological advances, Zhang posits that these tools are strategically imperative for navigating the complexities of the digital media landscape and big data analysis, and they provide powerful methodologies empowering researchers to uncover nuanced insights and trends within the vast expanse of digital information. Although this can be a daunting notion for researchers without a formal background in mathematics or computer science, this book highlights the substantial rewards of investing time and effort into the endeavor – mastery of ML and AI not only facilitates more sophisticated big data analyses, but also fosters interdisciplinary collaborations, enhancing the richness and depth of research outcomes. This book will serve as a foundational resource for communication scholars by providing essential knowledge and techniques to effectively leverage ML and AI at the intersection of communication research and data science.

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.

An authoritative survey of different contexts, methodologies, and theories of applied communication The field of Applied Communication Research (ACR) has made substantial progress over the past five decades in studying communication problems, and in making contributions to help solve them. Changes in society, human relationships, climate and the environment, and digital media have presented myriad contexts in which to apply communication theory. The Handbook of Applied Communication Research addresses a wide array of contemporary communication issues, their research implications in various contexts, and the challenges and opportunities for using communication to manage problems. This innovative work brings together the diverse perspectives of a team of notable international scholars from across disciplines. The Handbook of Applied Communication Research includes discussion and analysis spread across two comprehensive volumes. Volume one introduces ACR, explores what is possible in the field, and examines theoretical perspectives, organizational communication, risk and crisis communication, and media, data, design, and technology. The second volume focuses on real-world communication topics such as health and education communication, legal, ethical, and policy issues, and volunteerism, social justice, and communication activism. Each chapter addresses a specific issue or concern, and discusses the choices faced by participants in the communication process. This important contribution to communication research: Explores how various communication contexts are best approached Addresses balancing scientific findings with social and cultural issues Discusses how and to what extent media can mitigate the effects of adverse events Features original findings from ongoing research programs and original communication models and frameworks Presents the best available research and insights on where current research and best practices should move in the future A major addition to the body of knowledge in the field, The Handbook of Applied Communication Research is an invaluable work for advanced undergraduate students, graduate students, and scholars.

This book explores the changes in political communication in light of the development of a public opinion mediated by web 2.0 technologies. One of the most important changes in political communication is related to the process of disintermediation, i.e. the process by which digital technologies allow citizens to compete in the public space with those agents who, traditionally, co-opted public opinion. However, while disintermediation has undeniably generated a number of advances, having linked citizens to the public debate, the authors highlight some aspects where disintermediation is moving away from a rational and inclusive public space. They argue that these aspects, related to the immediacy, polarization and incivility of the communication, obscure the possibilities for democratization of digital political communication.

This volume explores the diverse applications of advanced tools and technologies of the emerging field of big data and their evidential value in business. It examines the role of analytics tools and methods of using big data in strengthening businesses to meet today’s information challenges and shows how businesses can adapt big data for effective businesses practices. This volume shows how big data and the use of data analytics is being effectively adopted more frequently, especially in companies that are looking for new methods to develop smarter capabilities and tackle challenges in dynamic processes. Many illustrative case studies are presented that highlight how companies in every sector are now focusing on harnessing data to create a new way of doing business.

Big Data for Qualitative Research covers everything small data researchers need to know about big data, from the potentials of big data analytics to its methodological and ethical challenges. The data that we generate in everyday life is now digitally mediated, stored, and analyzed by web sites, companies, institutions, and governments. Big data is large volume, rapidly generated, digitally encoded information that is often related to other networked data, and can provide valuable evidence for study of phenomena. This book explores the potentials of qualitative methods and analysis for big data, including text mining, sentiment analysis, information and data visualization, netnography, follow-the-thing methods, mobile research methods, multimodal analysis, and rhythmanalysis. It debates new concerns about ethics, privacy, and dataveillance for big data qualitative researchers. This book is essential reading for those who do qualitative and mixed methods research, and are curious, excited, or even skeptical about big data and what it means for future research. Now is the time for researchers to understand, debate, and envisage the new possibilities and challenges of the rapidly developing and dynamic field of big data from the vantage point of the qualitative researcher.

This book presents the outcomes of the 2021 International Conference on Cyber Security Intelligence and Analytics (CSIA 2021), an international conference dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly focusing on threat intelligence, analytics, and countering cybercrime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings and novel techniques, methods and applications on all aspects of cyber security intelligence and analytics. Due to COVID-19, Authors, Keynote Speakers and PC committees will attend the conference online.