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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.

Social sciences (general) --- Complex analysis --- Numerical analysis --- Applied physical engineering --- Computer science --- Programming --- Computer architecture. Operating systems --- Information systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- toegepaste wiskunde --- complexe analyse (wiskunde) --- applicatiebeheer --- apps --- computers --- informatica --- sociale wetenschappen --- database management --- gegevensanalyse --- computerkunde --- architectuur (informatica) --- data acquisition

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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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Networks play a central role in today’s society, since many sectors employing information technology, such as communication, mobility, and transport - even social interactions and political activities - are based on and rely on networks. In these times of globalization and the current global financial crisis with its complex and nearly incomprehensible entanglements of various structures and its huge effect on seemingly unrelated institutions and organizations, the need to understand large networks, their complex structures, and the processes governing them is becoming more and more important. This state-of-the-art survey reports on the progress made in selected areas of this important and growing field, thus helping to analyze existing large and complex networks and to design new and more efficient algorithms for solving various problems on these networks since many of them have become so large and complex that classical algorithms are not sufficient anymore. This volume emerged from a research program funded by the German Research Foundation (DFG) consisting of projects focusing on the design of new discrete algorithms for large and complex networks. The 18 papers included in the volume present the results of projects realized within the program and survey related work. They have been grouped into four parts: network algorithms, traffic networks, communication networks, and network analysis and simulation.

Algorithms. --- Computer networks. --- Algorism --- Algebra --- Arithmetic --- Foundations --- Communication systems, Computer --- Computer communication systems --- Data networks, Computer --- ECNs (Electronic communication networks) --- Electronic communication networks --- Networks, Computer --- Teleprocessing networks --- Data transmission systems --- Digital communications --- Electronic systems --- Information networks --- Telecommunication --- Cyberinfrastructure --- Electronic data processing --- Network computers --- Distributed processing --- Computer science. --- Computer Communication Networks. --- Information theory. --- Computer software. --- Computational complexity. --- Electronic data processing. --- Programming Techniques. --- Theory of Computation. --- Algorithm Analysis and Problem Complexity. --- Discrete Mathematics in Computer Science. --- Numeric Computing. --- ADP (Data processing) --- Automatic data processing --- Data processing --- EDP (Data processing) --- IDP (Data processing) --- Integrated data processing --- Computers --- Office practice --- Complexity, Computational --- Machine theory --- Software, Computer --- Computer systems --- Communication theory --- Communication --- Cybernetics --- Informatics --- Science --- Automation --- Computer programming. --- Computer communication systems. --- Computers. --- Computer science—Mathematics. --- Numerical analysis. --- Mathematical analysis --- Automatic computers --- Automatic data processors --- Computer hardware --- Computing machines (Computers) --- Electronic brains --- Electronic calculating-machines --- Electronic computers --- Hardware, Computer --- Calculators --- Cyberspace --- Electronic computer programming --- Electronic digital computers --- Programming (Electronic computers) --- Coding theory --- Programming --- Discrete mathematics. --- Numerical Analysis. --- Discrete mathematical structures --- Mathematical structures, Discrete --- Structures, Discrete mathematical --- Numerical analysis

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Networks play a central role in today's society, since many sectors employing information technology, such as communication, mobility, and transport - even social interactions and political activities - are based on and rely on networks. In these times of globalization and the current global financial crisis with its complex and nearly incomprehensible entanglements of various structures and its huge effect on seemingly unrelated institutions and organizations, the need to understand large networks, their complex structures, and the processes governing them is becoming more and more important. This state-of-the-art survey reports on the progress made in selected areas of this important and growing field, thus helping to analyze existing large and complex networks and to design new and more efficient algorithms for solving various problems on these networks since many of them have become so large and complex that classical algorithms are not sufficient anymore. This volume emerged from a research program funded by the German Research Foundation (DFG) consisting of projects focusing on the design of new discrete algorithms for large and complex networks. The 18 papers included in the volume present the results of projects realized within the program and survey related work. They have been grouped into four parts: network algorithms, traffic networks, communication networks, and network analysis and simulation.

Complex analysis --- Discrete mathematics --- Computer science --- Computer architecture. Operating systems --- Artificial intelligence. Robotics. Simulation. Graphics --- Computer. Automation --- discrete wiskunde --- complexe analyse (wiskunde) --- grafische vormgeving --- informatica --- algoritmen --- KI (kunstmatige intelligentie) --- computernetwerken --- numerieke analyse