This is the first textbook on social network analysis integrating theory, applications, and professional software for performing network analysis (Pajek). Pajek software and datasets for all examples are freely available, so the reader can learn network analysis by doing it. In addition, each chapter offers case studies for practicing network analysis. The book will enable the reader to gain the knowledge, skills, and tools to apply social network analysis in all social sciences, ranging from anthropology and sociology to business administration and history. ======== Table of contents Part I. Fundamentals 1. Looking for social structure 2. Attributes and relations Part II. Cohesion 3. Cohesive subgroups 4. Sentiments and friendship 5. Affiliations Part III. Brokerage 6. Center and periphery 7. Brokers and bridges 8. Diffusion Part IV. Ranking 9. Prestige 10. Ranking 11. Genealogies and citations Part V. Roles 12. Blockmodels Appendix 1. Getting started with Pajek Appendix 2. Exporting visualizations Appendix 3. Shortcur Key Combinations

对各种复杂网络的定量与定性特征的科学理解已成为网络时代科学研究中一个极其重要的挑战性课题，网络科学就是一门正在兴起的面对这一挑战的交叉性学科。本书致力于系统地介绍网络科学的基本概念、思想和方法，使得具有高等数学基础的读者都能够看懂，并具备把网络科学方法用于实际网络分析的能力。为此，本书没有过多地陷入数学和物理推导，而是更为关注网络科学的思维习惯和研究方式。本书在概要介绍了网络科学的背景和研究意义之后，分为四个部分详细介绍了网络基本概念、网络拓扑性质、网络拓扑模型和网络动力学。 本书适合作为研究生和高年级本科生的网络科学教材，也可供自然科学、工程技术科学和社会科学领域的研究人员与学生参考。

The scientific study of networks, including computer networks, social networks, and biological networks, has received an enormous amount of interest in the last few years. The rise of the Internet and the wide availability of inexpensive computers have made it possible to gather and analyze network data on a large scale, and the development of a variety of new theoretical tools has allowed us to extract new knowledge from many different kinds of networks. The study of networks is broadly interdisciplinary and important developments have occurred in many fields, including mathematics, physics, computer and information sciences, biology, and the social sciences. This book brings together for the first time the most important breakthroughs in each of these fields and presents them in a coherent fashion, highlighting the strong interconnections between work in different areas. Subjects covered include the measurement and structure of networks in many branches of science, methods for analyzing network data, including methods developed in physics, statistics, and sociology, the fundamentals of graph theory, computer algorithms, and spectral methods, mathematical models of networks, including random graph models and generative models, and theories of dynamical processes taking place on networks.

本书致力于系统地介绍分析复杂网络和人类行为动力学的演化模型和理论方法；涉及到的模型均给出解析过程和模拟，大部分模型给出了实证。力图体现理论研究上有深度、模型与实证相结合。第一部分以图、随机图和复杂网络为主线，本书拓展了随机图模型，将小世界网络的WS模型纳入了随机图的框架，给出了复杂网络的数学定义。以Poisson过程为基础，力求分析严谨、并且使应用工作者容易接受的解析过程。将适应度模型，加权网络统一在竞争网络模型下处理。基于随机服务系统对节点具有寿命的网络分类与分析。给出了变速增长网络模型，论述了幂律分布和几何级数增长网络度分布的计算。第二部分首先论述了基于排队系统的人类行为动力学模型。其次，在几类人类行为动力学的实证研究基础上，利用非齐次Poisson过程分析了人类行为动力学模型。提出了采购行为动力学模型，对采购订单的预测有一定的积极意义。最后，讨论了人类行为动力学中的分形与自相似性。

《普通高等教育"十二五"规划教材•高等院校重点推荐教材:复杂网络基础理论》讲述了科学根植在理论基础之上。理论是对经验现象或事实的科学解说和系统解释。顾名思义，复杂网络作为一门新兴科学，是对存在的网络现象及其复杂性进行解释的学科。首先，它研究的是网络现象。网络在自然界和人类社会中普遍存在，包括自然界中天然存在的星系、食物链网络、神经网络、蛋白质网络；人类社会中存在的社交网络、传染病传播网络、知识传播网络；人类创造的交通网络、通信网络、计算机网络等。