摘要：本文提供了復雜網絡領域的一些最重要的概念以及其在各學科的一些經典和最新的應用。第2節(jié)介紹了社會網絡，概述了傳統(tǒng)的分析方法。第3節(jié)涉及了技術的問題和社會網絡在實地考察研究中出現(xiàn)的問題。作為在該領域的研究人員，我們在第4節(jié)討論了最近一些對于傳統(tǒng)的社會網絡分析技術和思想的批判，以解決他們的動態(tài)。最后，在第5節(jié)討論了社會網絡研究中使用的代理模型。
關鍵詞：復雜性；復雜網絡；基于代理的社會網絡
一、復雜網絡理論
本節(jié)開頭試圖解釋相關領域的研究人員所定義的復雜性。一般來說我們提出“復雜網絡”，接著討論最重要的特征網絡。結尾部分簡要說明了最近復雜網絡理論在多學科的應用。現(xiàn)實世界的很多應用網絡規(guī)模龐大，在被稱為“復雜網絡”下產生了多學科研究的新高潮。長期傘的大小，結構相似性和動態(tài)的觀測網絡，這些屬于從自然物理科學到網絡社會科學的多種學科。在過去十年里，對復雜網絡的研究取得了非凡的進步。 這個研究已經解決了網絡特征的識別及其相應的解決措施。全面綜述可能被紐曼（2003年），阿爾貝和Barabási（2002年）發(fā)布。
1.1 復雜性和復雜網絡
洞穴項目的關鍵是“解決復雜性”，這可能有助于提出該項目目標的概念。網絡出現(xiàn)時，子系統(tǒng)或社會制度，作用物，就有一些關系。復雜網絡的這個概念到現(xiàn)在已經存在了將近10年,我們在隨后的一節(jié)討論。
1.1.1 復雜性
首先，韋氏字典（2005）定義的“復雜”一詞（我們挑最相關的變體）定義：復雜性
“一個群體相關一個單一的活動(如狩獵),進程(比如使用燧石),或文明單位(1)的文化特質:一組被壓制下去的欲望和記憶的對人格獨特的影響(2):一個對一種情況和主題的夸張反應:一群相關單位的明顯程度與自然的關系所知仍屬有限的。
Abstract
This review provides a survey of some of the most important concepts in the field of the so-called 'complex networks', and some classical and recent applications in various disciplines. Social networks are introduced in Section 2, and an overview of the traditional analysis techniques is presented. Section 3 addresses the issue of the techniques and issues that arise in the fieldwork research about social networks. We discuss, in Section 4, some recent critique of the traditional social networks analyses techniques and the ideas to tackle their dynamics, as presented researchers in the field. Finally, Section 5 discusses the used of agent-based modeling in the study of social networks.
Keywords: Complexity, complex networks, agent-based social networks
1. Theory of Complex Networks
This section begins with an attempt to explain complexity as defined by researchers in the relevant fields.We present the notion of 'complex networks' in general, followed by a discussion on the most important characteristic networks. The section ends with a quick overview of some recent applications of the complex networks theory in various disciplines.
The enormity of the size of networks in quite a few real-world applications, gave rise to a new surge in multidisciplinary research under the term called 'complex networks'. The term umbrellas the size, similarity of structure and dynamics in the observed networks, which belong to a variety of disciplines, from natural and physical sciences, social sciences to the Web.In the last decade, extraordinary advancements have been made in the studies of complex networks. The studies have resulted in identifying characteristic networks and their relevant measures. A comprehensive review may be found in (Newman, 2003; Albert and Barabás