Digital media presents an array of interesting challenges adapting new modes of collaborative, online communication to traditional writing and literary practices at the practical and theoretical levels. For centuries, popular concepts of the modern author, regardless of genre, have emphasized writing as a solo exercise in human communication, while the act of reading remains associated with solitude and individual privacy. “The Community and the Algorithm: A Digital Interactive Poetics” explores important cultural changes in these relationships thanks to the rapid development of digital internet technologies allowing near-instantaneous, synchronous, multimedia interaction across the globe. The radical shift in how we author and consume media as an online, electronic transmission effectively resituates the writing process across the liberal arts as less a solitary act of individual enquiry and reflection, and more an ongoing, collaborative process of creative interaction within a multimedia environment or network. Contributions in this anthology demonstrate a robust history and equally diverse contemporary approach to multimedia interaction for literary and artistic ends. Central to all media formats, computation is explored throughout this volume to critically examine how algorithmic procedures in writing help bring forward many key concepts to building creative communities in a digital environment. Each chapter in this book accordingly introduces readers to various new collaborative experiments using a broad range of different digital media formats, including VR, Natural Language Generation (NLG), and metagaming tools. This book will appeal broadly to students, instructors, and independent artists working in the digital arts, while its emphasis on social interactivity will interest theorists and teachers working in theatre, social media, and cyberpsychology. Its secondary focus on computation and media programming as a site of artistic experimentation will also interest programmers and web designers at various professional levels.

This book constitutes the refereed proceedings of the 10th IFIP TC 12 International Conference on Intelligent Information Processing, IIP 2018, held in Nanning, China, in October 2018. The 37 full papers and 8 short papers presented were carefully reviewed and selected from 80 submissions. They are organized in topical sections on machine learning, deep learning, multi-agent systems, neural computing and swarm intelligence, natural language processing, recommendation systems, social computing, business intelligence and security, pattern recognition, and image understanding.

This book presents the latest research advances in complex network structure analytics based on computational intelligence (CI) approaches, particularly evolutionary optimization. Most if not all network issues are actually optimization problems, which are mostly NP-hard and challenge conventional optimization techniques. To effectively and efficiently solve these hard optimization problems, CI based network structure analytics offer significant advantages over conventional network analytics techniques. Meanwhile, using CI techniques may facilitate smart decision making by providing multiple options to choose from, while conventional methods can only offer a decision maker a single suggestion. In addition, CI based network structure analytics can greatly facilitate network modeling and analysis. And employing CI techniques to resolve network issues is likely to inspire other fields of study such as recommender systems, system biology, etc., which will in turn expand CI’s scope and applications. As a comprehensive text, the book covers a range of key topics, including network community discovery, evolutionary optimization, network structure balance analytics, network robustness analytics, community-based personalized recommendation, influence maximization, and biological network alignment. Offering a rich blend of theory and practice, the book is suitable for students, researchers and practitioners interested in network analytics and computational intelligence, both as a textbook and as a reference work.

This volume constitutes the proceedings of the 10th International Conference on Hybrid Artificial Intelligent Systems, HAIS 2015, held Bilbao, Spain, June 2014. The 60 papers published in this volume were carefully reviewed and selected from 190 submissions. They are organized in topical sections such as data mining and knowledge discovery; video and image analysis; bio-inspired models and evolutionary computation; learning algorithms; hybrid intelligent systems for data mining and applications; classification and cluster analysis, HAIS applications.

This book constitutes the proceedings of the 9th International Symposium on Foundations of Information and Knowledge Systems, FoIKS 2016, held in Linz, Austria, in March 2016. The 14 revised full papers presented papers were carefully reviewed and selected from 23 submissions. The papers address various topics such as reasoning about beliefs, uncertainty, incompleteness, and inconsistency, inference and problem solving, querying and pattern mining, dealing with knowledge, logics and complexity.

This book covers computationally innovative methods and technologies including data collection and elicitation, data processing, data analysis, data visualizations, and data presentation. It explores how digital humanists have harnessed the hypersociality and social technologies, benefited from the open-source sharing not only of data but of code, and made technological capabilities a critical part of humanities work. Chapters are written by researchers from around the world, bringing perspectives from diverse fields and subject areas. The respective authors describe their work, their research, and their learning. Topics include semantic web for cultural heritage valorization, machine learning for parody detection by classification, psychological text analysis, crowdsourcing imagery coding in natural disasters, and creating inheritable digital codebooks.Designed for researchers and academics, this book is suitable for those interested in methodologies and analytics that can be applied in literature, history, philosophy, linguistics, and related disciplines. Professionals such as librarians, archivists, and historians will also find the content informative and instructive.

Computational approaches offer exciting opportunities for us to do social science differently. This beginner’s guide discusses a range of computational methods and how to use them to study the problems and questions you want to research. It assumes no knowledge of programming, offering step-by-step guidance for coding in Python and drawing on examples of real data analysis to demonstrate how you can apply each approach in any discipline. The book also: Considers important principles of social scientific computing, including transparency, accountability and reproducibility. Understands the realities of completing research projects and offers advice for dealing with issues such as messy or incomplete data and systematic biases. Empowers you to learn at your own pace, with online resources including screencast tutorials and datasets that enable you to practice your skills and get up to speed. For anyone who wants to use computational methods to conduct a social science research project, this book equips you with the skills, good habits and best working practices to do rigorous, high quality work.

The book is a collection of high-quality peer-reviewed research papers presented at the Fifth International Conference on Innovations in Computer Science and Engineering (ICICSE 2017) held at Guru Nanak Institutions, Hyderabad, India during 18-19 August 2017. The book discusses a wide variety of industrial, engineering and scientific applications of the engineering techniques. Researchers from academic and industry present their original work and exchange ideas, information, techniques and applications in the field of Communication, Computing and Data Science and Analytics.

Until recently, measurable dynamics has been held as a highly theoretcal mathematical topic with few generally known obvious links for practitioners in areas of applied mathematics. However, the advent of high-speed computers, rapidly developing algorithms, and new numerical methods has allowed for a tremendous amount of progress and sophistication in efforts to represent the notion of a transfer operator discretely but to high resolution. This book connects many concepts in dynamical systems with mathematical tools from areas such as graph theory and ergodic theory. The authors introduce practical tools for applications related to measurable dynamical systems, coherent structures, and transport problems. The new and fast-developing computational tools discussed throughout the book allow for detailed analysis of real-world problems that are simply beyond the reach of traditional methods.