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Modern computer power and high-precision observational data have greatly improved the reliability of meteoroid stream models. At present, scientific research calls for two kinds of models: precise ones for individual streams, and statistically averaged ones for Solar System dust distribution models. Thus, there is a wide field of study open to stream modellers. This brief describes step-by-step computer simulations of meteoroid stream formation and evolution. Detailed derivations of relevant formulae are given, along with plenty of helpful, digestible figures explaining the subtleties of the method. Each theoretical section ends with examples aimed to help readers practice and master the material. Most of the examples are based on the Geminid meteoroid stream model, which has been developed by the author in the last 30 years. The book is intended for researchers interested in meteor astronomy and mathematical modelling, and it is also accessible to physics and astrophysics students.

Astrophysics. --- Mathematical physics. --- Sociophysics. --- Econophysics. --- Theoretical Astrophysics. --- Astrophysics and Astroparticles. --- Data-driven Science, Modeling and Theory Building. --- Physical mathematics --- Physics --- Mathematical sociology --- Statistical physics --- Astronomical physics --- Astronomy --- Cosmic physics --- Economics --- Mathematics --- Statistical methods

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This book presents a perspective of network analysis as a tool to find and quantify significant structures in the interaction patterns between different types of entities. Moreover, network analysis provides the basic means to relate these structures to properties of the entities. It has proven itself to be useful for the analysis of biological and social networks, but also for networks describing complex systems in economy, psychology, geography, and various other fields. Today, network analysis packages in the open-source platform R and other open-source software projects enable scientists from all fields to quickly apply network analytic methods to their data sets. Altogether, these applications offer such a wealth of network analytic methods that it can be overwhelming for someone just entering this field. This book provides a road map through this jungle of network analytic methods, offers advice on how to pick the best method for a given network analytic project, and how to avoid common pitfalls. It introduces the methods which are most often used to analyze complex networks, e.g., different global network measures, types of random graph models, centrality indices, and networks motifs. In addition to introducing these methods, the central focus is on network analysis literacy – the competence to decide when to use which of these methods for which type of question. Furthermore, the book intends to increase the reader's competence to read original literature on network analysis by providing a glossary and intensive translation of formal notation and mathematical symbols in everyday speech. Different aspects of network analysis literacy – understanding formal definitions, programming tasks, or the analysis of structural measures and their interpretation – are deepened in various exercises with provided solutions. This text is an excellent, if not the best starting point for all scientists who want to harness the power of network analysis for their field of expertise.

Application software. --- Physics. --- Computational complexity. --- Sociophysics. --- Econophysics. --- Data mining. --- Computer Appl. in Social and Behavioral Sciences. --- Applications of Graph Theory and Complex Networks. --- Complexity. --- Data-driven Science, Modeling and Theory Building. --- Data Mining and Knowledge Discovery.

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The Encyclopedia of Social Network Analysis and Mining (ESNAM) is the first major reference work to integrate fundamental concepts and research directions in the areas of social networks and  application to data mining. This set of comprehensive and authoritative volumes •         explains the science and technology behind the rapidly growing global avenues for exchanging views and influencing others •         presents the first comprehensive coverage of all fields that contribute  to social network construction and analysis as a multidisciplinary domain •         is designed to appeal to an interdisciplinary audience ranging from the  undergraduate to professional level •         describes social network applications to knowledge mining and discovery •         addresses privacy, security, ethical, and civil liberty issues for social networks. While ESNAM  reflects the state-of-the-art in  social network research, the field  had its start in the 1930s when fundamental issues in social network research were broadly defined. These communities were limited to relatively small numbers of nodes (actors) and links. More recently the advent of electronic communication, and in particular on-line communities, have created social networks of hitherto unimaginable sizes. People around the world are directly or indirectly connected by popular social networks established using web-based platforms rather than by physical proximity. Reflecting the interdisciplinary nature of this unique field, the essential contributions of diverse disciplines, from computer science, mathematics, and statistics to sociology and behavioral science, are described among the 300 authoritative yet highly readable entries. Students will find a world of information and insight behind the familiar façade of the social networks in which they participate. Researchers and practitioners will benefit from a comprehensive perspective on the methodologies for analysis of constructed networks, and the data mining and machine learning techniques that have proved attractive for sophisticated knowledge discovery in complex applications. Also addressed is the application of social network methodologies to other domains, such as web networks and biological networks.

Computer communication systems. --- Sociology. --- Sociophysics. --- Econophysics. --- Bioinformatics. --- Computers and civilization. --- System safety. --- Computer Communication Networks. --- Sociology, general. --- Data-driven Science, Modeling and Theory Building. --- Computers and Society. --- Security Science and Technology.

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population data science --- Population Characteristics. --- Data Science. --- Data Analytics --- Data-Driven Science --- Analytic, Data --- Analytics, Data --- Data Analytic --- Data Driven Science --- Data Sciences --- Data-Driven Sciences --- Science, Data --- Science, Data-Driven --- Sciences, Data --- Sciences, Data-Driven --- Big Data --- Population Heterogeneity --- Population Statistics --- Characteristic, Population --- Characteristics, Population --- Heterogeneity, Population --- Population Characteristic --- Statistics, Population --- Population --- Population forecasting --- Forecasting, Population --- Population projection --- Population projections --- Projection, Population --- Projections, Population --- Social prediction --- Forecasting --- Population forecasting. --- Population. --- Human population --- Human populations --- Population growth --- Populations, Human --- Economics --- Human ecology --- Sociology --- Demography --- Malthusianism

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This introductory text is devoted to exposing the underlying nature of price formation in financial markets as a predominantly sociological phenomenon that relates individual decision-making to emergent and co-evolving social and financial structures. Two different levels of this sociological influence are considered: First, we examine how price formation results from the social dynamics of interacting individuals, where interaction occurs either through the price or by direct communication.  Then the same processes are revisited and examined at the level of larger groups of individuals. In this book, models of both levels of socio-finance are presented, and it is shown, in particular, how complexity theory provides the conceptual and methodological tools needed to understand and describe such phenomena. Accordingly, readers are first given a broad introduction to the standard economic theory of rational financial markets and will come to understand its shortcomings with the help of concrete examples. Complexity theory is then introduced in order to properly account for behavioral decision-making and match the observed market dynamics. This book is conceived as a primer for newcomers to the field, as well as for practitioners seeking new insights into the field of complexity science applied to socio-economic systems in general, and financial markets and price formation in particular.

Finance --- Business & Economics --- Finance - General --- Economics, Mathematical. --- Sociophysics. --- Econophysics. --- Macroeconomics. --- Economics. --- Macroeconomics/Monetary Economics//Financial Economics. --- Socio- and Econophysics, Population and Evolutionary Models. --- Quantitative Finance. --- Finance. --- Data-driven Science, Modeling and Theory Building. --- Funding --- Funds --- Economics --- Currency question --- Social aspects. --- Economics, Mathematical . --- Statistical physics --- Mathematical sociology --- Mathematical economics --- Econometrics --- Mathematics --- Statistical methods --- Methodology