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Explains numerous informetric regularities based on a decreasing power law as size-frequency function, i.e. Lotka's law. It revives the historical formulation of Alfred Lotka of 1926 and shows the power of this power law, both in classical aspects of informetrics (libraries, bibliographies) and in 'new' applications such as social networks.
This monograph is a comprehensive and cohesive exposition of power-law statistics. Following a bottom-up construction from a foundational bedrock – the power Poisson process – this monograph presents a unified study of an assortment of power-law statistics including: Pareto laws, Zipf laws, Weibull and Fréchet laws, power Lorenz curves, Lévy laws, power Newcomb-Benford laws, sub-diffusion and super-diffusion, and 1/f and flicker noises. The bedrock power Poisson process, as well as the assortment of power-law statistics, are investigated via diverse perspectives: structural, stochastic, fractal, dynamical, and socioeconomic. This monograph is poised to serve researchers and practitioners – from various fields of science and engineering – that are engaged in analyses of power-law statistics.
Through different theoretical and analyses glasses, this book critically examines the organization of knowledge as it is involved in matters of digital communication, the social, cultural, and political consequences of classifying, and how particular historical contexts shape ideas of information and what information to classify and record.
Dealing with information is one of the vital skills in the 21st century. It takes a fair degree of information savvy to create, represent and supply information as well as to search for and retrieve relevant knowledge. How does information (documents, pieces of knowledge) have to be organized in order to be retrievable? What role does metadata play? What are search engines on the Web, or in corporate intranets, and how do they work? How must one deal with natural language processing and tools of knowledge organization, such as thesauri, classification systems, and ontologies? How useful is social tagging? How valuable are intellectually created abstracts and automatically prepared extracts? Which empirical methods allow for user research and which for the evaluation of information systems? This Handbook is a basic work of information science, providing a comprehensive overview of the current state of information retrieval and knowledge representation. It addresses readers from all professions and scientific disciplines, but particularly scholars, practitioners and students of Information Science, Library Science, Computer Science, Information Management, and Knowledge Management. This Handbook is a suitable reference work for Public and Academic Libraries.
Scientometrics have become an essential element in the practice and evaluation of science and research, including both the evaluation of individuals and national assessment exercises. Yet, researchers and practitioners in this field have lacked clear theories to guide their work. As early as 1981, then doctoral student Blaise Cronin published "The need for a theory of citing" —a call to arms for the fledgling scientometric community to produce foundational theories upon which the work of the field could be based. More than three decades later, the time has come to reach out the field again and ask how they have responded to this call. This book compiles the foundational theories that guide informetrics and scholarly communication research. It is a much needed compilation by leading scholars in the field that gathers together the theories that guide our understanding of authorship, citing, and impact.
New Research in Information Behaviour provides an understanding of the new directions, leading edge theories and models in information behaviour. Information behaviour is conceptualized as complex human information related processes that are embedded within an individual's everyday social and life processes.
This book presents scientific metrics and its applications for approaching scientific findings in the field of Physics, Economics and Scientometrics. Based on a collection of the author’s publications in these fields, the book reveals the profound links between the measures and the findings in the natural laws, from micro-particles to macro-cosmos, in the economic rules of human society, and in the core knowledge among mass information. With this book the readers can gain insights or ideas on addressing the questions of how to measure the physical world, economics process and human knowledge, from the perspective of scientific metrics. The book is also useful to scientists, particularly to specialists in physics, economics and scientometrics, for promoting and stimulating their creative ideas based on scientific metrics.
This book deals with methods to evaluate scientific productivity. In the book statistical methods, deterministic and stochastic models and numerous indexes are discussed that will help the reader to understand the nonlinear science dynamics and to be able to develop or construct systems for appropriate evaluation of research productivity and management of research groups and organizations. The dynamics of science structures and systems is complex, and the evaluation of research productivity requires a combination of qualitative and quantitative methods and measures. The book has three parts. The first part is devoted to mathematical models describing the importance of science for economic growth and systems for the evaluation of research organizations of different size. The second part contains descriptions and discussions of numerous indexes for the evaluation of the productivity of researchers and groups of researchers of different size (up to the comparison of research productivities of research communities of nations). Part three contains discussions of non-Gaussian laws connected to scientific productivity and presents various deterministic and stochastic models of science dynamics and research productivity. The book shows that many famous fat tail distributions as well as many deterministic and stochastic models and processes, which are well known from physics, theory of extreme events or population dynamics, occur also in the description of dynamics of scientific systems and in the description of the characteristics of research productivity. This is not a surprise as scientific systems are nonlinear, open and dissipative.
This landmark textbook takes a whole subject approach to Information Science as a discipline. Introduced by leading international scholars and offering a global perspective on the discipline, this is designed to be the standard text for students worldwide. The authors' expert narrative guides you through each of the essential building blocks of information science offering a concise introduction and expertly chosen further reading and resources. Critical topics covered include: foundations: - concepts, theories and historical perspectives - organising and retrieving information - information behaviour, domain analysis and digital literacies - technologies, digital libraries and information management - information research methods and informetrics - changing contexts: information society, publishing, e-science and digital humanities - the future of the discipline. Readership: Students of information science, information and knowledge management, librarianship, archives and records management worldwide. Students of other information-related disciplines such as museum studies, publishing, and information systems and practitioners in all of these disciplines.
Covers the development, design, and utilization of virtual organizations and communities and the resulting impact of these venues.