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In the world of Facebook, Twitter and Yelp, water-cooler conversations with co-workers and backyard small talk with neighbors have moved from the physical world to the digital arena. In this new landscape, organizations ranging from Fortune 500 companies to government agencies to political campaigns continuously monitor online opinions in an effort to guide their actions. Are consumers satisfied with our product? How are our policies perceived? Do voters agree with our platform? Measuring online opinion is more complex than just reading a few posted reviews. Social media is replete with noise and chatter that can contaminate monitoring efforts. By knowing what shapes online opinions, organizations can better uncover the valuable insights hidden in the social media chatter and better inform strategy. This book can help anyone facing the challenge of making sense of social media data to move beyond the current practice of social media monitoring to a more comprehensive use of social media intelligence.
Organizations today need to continually implement new strategies that increase the sustainability and competitiveness of a business. By sharing experiences in a collaborative environment where the collective experience of its membership can lead to the design and implementation of new technology and product improvement, a company can differentiate itself to successfully compete in the business realm. Strategic Collaborative Innovations in Organizational Systems is a collection of research on the methods and applications of collaborative strategies in advancing the efficiency and effectiveness of a firm. Highlighting a range of topics including organizational design, productivity strategies, and workforce diversity, this book is ideally designed for academicians, business managers, entrepreneurs, human resources managers, researchers, graduate students, and scholars seeking current research on business and competitive strategies within a collaborative and organizational context.
Will your next doctor be a human being—or a machine? Will you have a choice? If you do, what should you know before making it?This book introduces the reader to the pitfalls and promises of artificial intelligence (AI) in its modern incarnation and the growing trend of systems to "reach off the Web" into the real world. The convergence of AI, social networking, and modern computing is creating an historic inflection point in the partnership between human beings and machines with potentially profound impacts on the future not only of computing but of our world and species.AI experts and researchers James Hendler—co-originator of the Semantic Web (Web 3.0)—and Alice Mulvehill—developer of AI-based operational systems for DARPA, the Air Force, and NASA—explore the social implications of AI systems in the context of a close examination of the technologies that make them possible. The authors critically evaluate the utopian claims and dystopian counterclaims of AI prognosticators. Social Machines: The Coming Collision of Artificial Intelligence, Social Networking, and Humanity is your richly illustrated field guide to the future of your machine-mediated relationships with other human beings and with increasingly intelligent machines. What Readers Will Learn What the concept of a social machine is and how the activities of non-programmers are contributing to machine intelligence How modern artificial intelligence technologies, such as Watson, are evolving and how they process knowledge from both carefully produced information (such as Wikipedia and journal articles) and from big data collections The fundamentals of neuromorphic computing, knowledge graph search, and linked data, as well as the basic technology concepts that underlie networking applications such as Facebook and Twitter How the change in attitudes towards cooperative work on the Web, especially in the younger demographic, is critical to the future of Web applications Who This Book Is ForGeneral readers and technically engaged developers, entrepreneurs, and technologists interested in the threats and promises of the accelerating convergence of artificial intelligence with social networks and mobile web technologies.
Artificial Intelligence has revolutionized and transformed Social Media in many innovative ways. With around 3 billion people connected to various social media platforms, they are generating a huge mass of data. Now the question is, “Why should social media be concerned about all this data floating around?” The answer to this question is that this ‘meta – data’ is of great value to social media platforms. One reason is that social networks can keep themselves relevant with times only if they keep themselves abreast about the needs, wants and choices of the users from multiple geographical locations. Another reason is that they get to monetize this information when they share their platforms with advertisers and marketers. AI is one single solution for both these scenarios.
This book shows how open source intelligence can be a powerful tool for combating crime by linking local and global patterns to help understand how criminal activities are connected. Readers will encounter the latest advances in cutting-edge data mining, machine learning and predictive analytics combined with natural language processing and social network analysis to detect, disrupt, and neutralize cyber and physical threats. Chapters contain state-of-the-art social media analytics and open source intelligence research trends. This multidisciplinary volume will appeal to students, researchers, and professionals working in the fields of open source intelligence, cyber crime and social network analytics. Chapter Automated Text Analysis for Intelligence Purposes: A Psychological Operations Case Study is available open access under a Creative Commons Attribution 4.0 International License via link.springer.com.
As consumers, we turn to the public arena of social media to share our opinions and learn about the opinions of others. Fortune 500 companies, political campaigns, government agencies and many other organizations constantly monitor social media to gauge public opinion. This book explains how opinions are formed, what affects the opinions posted online and how organizations can use social media to inform their strategies.
This ebook provides an overview of the power of social media intelligence for public safety. It explores the evolution of public safety and its challenges in the modern world, the impact of social media on public order, the risks and benefits of social media intelligence, and the strategies and tools for effective social media monitoring. This book also examines ethical considerations, privacy concerns, legal issues, and data quality in social media intelligence. Real examples are used to illustrate the value that Social Media Intelligence can bring for Public Safety and Public Order.
The global security environment, dominated and dependent on information and communication technology, generates an accumulation of disruptive factors for society. This volume, in direct accordance with technological developments that have facilitated information avalanche and (anonymous) communication, has required interdisciplinary research in areas such as: psychology, sociology, computer science, social media communication and legislation. The research aims to establish whether social media platforms, through the actions they facilitate, can pose risks and threats to national security and to identify premises in order to stimulate strategies that should be followed to avoid transforming various forms of online communication into a potentiating and generating factor of crime, radical or extremist opinions, mass manipulation, etc. At the same time, the research offers an alternative vision on approaching the concept of intelligence in the context of the development of social media networks (SocMInt) and promotes ways to improve and streamline how to achieve objectives that can be successfully applied, including in business intelligence. In this regard, a case study is conducted on the effects of CoVid-19 pandemic (SARS-CoV-2 coronavirus) from the perspective of law enforcement agencies. Although the individually exploitation of SocMInt does not provide a comprehensive answer, it must be used in the initial stages of decision-making and effort-making, due to the low costs compared to other Int disciplines. The volume does not present a solution to current problems, but through its didactic, documentary and informative nature it offers professional support at high standards to analysts and managers in decision making.
This volume provides the audience with an updated, in-depth and highly coherent material on the conceptually appealing and practically sound information technology of Computational Intelligence applied to the analysis, synthesis and evaluation of social networks. The volume involves studies devoted to key issues of social networks including community structure detection in networks, online social networks, knowledge growth and evaluation, and diversity of collaboration mechanisms. The book engages a wealth of methods of Computational Intelligence along with well-known techniques of linear programming, Formal Concept Analysis, machine learning, and agent modeling. Human-centricity is of paramount relevance and this facet manifests in many ways including personalized semantics, trust metric, and personal knowledge management; just to highlight a few of these aspects. The contributors to this volume report on various essential applications including cyber attacks detection, building enterprise social networks, business intelligence and forming collaboration schemes. Given the subject area, this book is aimed at a broad audience of researchers and practitioners. Owing to the nature of the material being covered and a way it is organized, the volume will appeal to the well-established communities including those active in various disciplines in which social networks, their analysis and optimization are of genuine relevance. Those involved in operations research, management, various branches of engineering, and economics will benefit from the exposure to the subject matter.