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在过去的四十年里，计算社会学诞生并且越来越受欢迎。这主要用于建模或构建社会过程的解释，并且依赖于从简单活动中'''涌现 Emergence'''的复杂行为。涌现背后的思想是，任何较大系统不总是必须和组成系统的部分具有一样的性质。引入涌现思想的人是亚历山大（Alexander）、摩根（Morgan）和布罗德（Broad），他们都是'''经典涌现主义者 Classical Emergentists'''。经典涌现主义者提出这个概念和方法的时间是在二十世纪初期。这种方法的目的是在还原论的唯物主义和二元论这两种不同的本体论之间找到一个足够好的调和。

在过去的四十年里，计算社会学诞生并且越来越受欢迎。这主要用于建模或构建社会过程的解释，并且依赖于从简单活动中'''涌现 Emergence'''的复杂行为。涌现背后的思想是，任何较大系统不总是必须和组成系统的部分具有一样的性质。引入涌现思想的人是亚历山大（Alexander）、摩根（Morgan）和布罗德（Broad），他们都是'''经典涌现主义者 Classical Emergentists'''。经典涌现主义者提出这个概念和方法的时间是在二十世纪初期。这种方法的目的是在还原论的唯物主义和二元论这两种不同的本体论之间找到一个足够好的调和。

 

（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）Following Émile Durkheim's call to analyze complex modern society sui generis）

（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）Following Émile Durkheim's call to analyze complex modern society sui generis）

的要求，战后结构功能主义社会学家如帕森斯（Talcott Parsons）利用这些组成部分之间系统和等级相互作用的理论，试图产生大统一的社会学理论，如 AGIL 范式。霍曼斯（George Homans）等社会学家认为，社会学理论应该被构建为具有命题和精确术语的等级结构的，并且从中可以得出能够在实证研究中被操作化的其他命题和假设。由于早在1956年计算机算法和程序就已经被用来测试和验证数学定理（如'''四色定理Four Color Theorem'''），一些学者预计相似的计算方法可以“解决”和“证明”类似的社会结构和动态的问题和定理。

的要求，战后结构功能主义社会学家如帕森斯（Talcott Parsons）利用这些组成部分之间系统和等级相互作用的理论，试图产生大统一的社会学理论，如 AGIL 范式。霍曼斯（George Homans）等社会学家认为，社会学理论应该被构建为具有命题和精确术语的等级结构，并且从中可以得出能够在实证研究中被操作化的其他命题和假设。由于早在1956年计算机算法和程序就已经被用来测试和验证数学定理（如'''四色定理Four Color Theorem'''），一些学者预计相似的计算方法可以“解决”和“证明”类似的社会结构和动态的问题和定理。

===Macrosimulation and microsimulation 宏观模拟和微观模拟===

===Macrosimulation and microsimulation 宏观模拟和微观模拟===

By the late 1960s and early 1970s, social scientists used increasingly available computing technology to perform macro-simulations of control and feedback processes in organizations, industries, cities, and global populations. These models used differential equations to predict population distributions as holistic functions of other systematic factors such as inventory control, urban traffic, migration, and disease transmission. Although simulations of social systems received substantial attention in the mid-1970s after the Club of Rome published reports predicting that policies promoting exponential economic growth would eventually bring global environmental catastrophe, the inconvenient conclusions led many authors to seek to discredit the models, attempting to make the researchers themselves appear unscientific. Hoping to avoid the same fate, many social scientists turned their attention toward micro-simulation models to make forecasts and study policy effects by modeling aggregate changes in state of individual-level entities rather than the changes in distribution at the population level. However, these micro-simulation models did not permit individuals to interact or adapt and were not intended for basic theoretical research.

By the late 1960s and early 1970s, social scientists used increasingly available computing technology to perform macro-simulations of control and feedback processes in organizations, industries, cities, and global populations. These models used differential equations to predict population distributions as holistic functions of other systematic factors such as inventory control, urban traffic, migration, and disease transmission. Although simulations of social systems received substantial attention in the mid-1970s after the Club of Rome published reports predicting that policies promoting exponential economic growth would eventually bring global environmental catastrophe, the inconvenient conclusions led many authors to seek to discredit the models, attempting to make the researchers themselves appear unscientific. Hoping to avoid the same fate, many social scientists turned their attention toward micro-simulation models to make forecasts and study policy effects by modeling aggregate changes in state of individual-level entities rather than the changes in distribution at the population level. However, these micro-simulation models did not permit individuals to interact or adapt and were not intended for basic theoretical research.

截至20世纪60年代末70年代初，社会科学家越来越多地使用已有的计算技术，在组织、工业、城市和全球人口中进行控制和反馈过程的'''宏观模拟 Macrosimulation''' 。这些模型使用微分方程作为其他系统因素的整体函数来预测人口分布，这些系统因素包括库存控制、城市交通、人口迁移和疾病传播等。20世纪70年代中期，罗马俱乐部(Club of Rome)发表报告预测，促进指数式经济增长的政策最终将导致全球环境灾难，这些令人不舒服的结论导致许多研究者试图反驳这些模型，试图让研究人员自己显得不那么科学。为了避免同样的情况，许多社会科学家将注意力转向'''微观模拟 Microsimulation'''模型。这些模型通过模拟个体状态的总体变化而不是总体人口级别的变化来进行预测和研究政策的效果。然而，这些微观模拟模型并不允许个体相互作用或适应、变化（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）变化是根据适应（adapt）加上去的，不知道是否合理），研究者也不打算将它们用于基础理论研究。

截至20世纪60年代末70年代初，社会科学家越来越多地使用已有的计算技术，在组织、工业、城市和全球人口中进行控制和反馈过程的'''宏观模拟 Macrosimulation''' 。这些模型使用微分方程作为其他系统因素的整体函数来预测人口分布，这些系统因素包括库存控制、城市交通、人口迁移和疾病传播等。20世纪70年代中期，罗马俱乐部(Club of Rome)发表报告预测，促进指数式经济增长的政策最终将导致全球环境灾难，这些令人不舒服的结论导致许多研究者试图反驳这些模型，试图让研究人员自己显得不那么科学。

为了避免同样的情况，许多社会科学家将注意力转向'''微观模拟 Microsimulation'''模型。这些模型通过模拟个体状态的总体变化而不是总体人口级别的变化来进行预测和研究政策的效果。然而，这些微观模拟模型并不允许个体相互作用或适应、变化（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]）变化是根据适应（adapt）加上去的，不知道是否合理），研究者也不打算将它们用于基础理论研究。

===Cellular automata and agent-based modeling 元胞自动机和基于主体建模===

===Cellular automata and agent-based modeling 元胞自动机和基于主体建模===

The 1970s and 1980s were also a time when physicists and mathematicians were attempting to model and analyze how simple component units, such as atoms, give rise to global properties, such as complex material properties at low temperatures, in magnetic materials, and within turbulent flows. Using cellular automata, scientists were able to specify systems consisting of a grid of cells in which each cell only occupied some finite states and changes between states were solely governed by the states of immediate neighbors. Along with advances in artificial intelligence and microcomputer power, these methods contributed to the development of "chaos theory" and "complexity theory" which, in turn, renewed interest in understanding complex physical and social systems across disciplinary boundaries. Research organizations explicitly dedicated to the interdisciplinary study of complexity were also founded in this era: the Santa Fe Institute was established in 1984 by scientists based at Los Alamos National Laboratory and the BACH group at the University of Michigan likewise started in the mid-1980s.

The 1970s and 1980s were also a time when physicists and mathematicians were attempting to model and analyze how simple component units, such as atoms, give rise to global properties, such as complex material properties at low temperatures, in magnetic materials, and within turbulent flows. Using cellular automata, scientists were able to specify systems consisting of a grid of cells in which each cell only occupied some finite states and changes between states were solely governed by the states of immediate neighbors. Along with advances in artificial intelligence and microcomputer power, these methods contributed to the development of "chaos theory" and "complexity theory" which, in turn, renewed interest in understanding complex physical and social systems across disciplinary boundaries. Research organizations explicitly dedicated to the interdisciplinary study of complexity were also founded in this era: the Santa Fe Institute was established in 1984 by scientists based at Los Alamos National Laboratory and the BACH group at the University of Michigan likewise started in the mid-1980s.

20世纪70年代和80年代，物理学家和数学家也在试图模拟和分析简单的组成单位，如原子，如何引起整体特性，比如在低温下，在磁性材料和湍流中的复杂材料特性。使用'''元胞自动机 Cellular Automata'''，科学家们能够指定由元胞网格组成的系统，其中每个元胞只占据一些有限的状态，状态之间的变化完全由相邻元胞的状态控制。随着人工智能和微型计算机能力的进步，这些方法促进了“混沌理论”和“复杂性理论”的发展，这反过来又重新引起了人们对跨学科的复杂物理和社会系统的兴趣。明确致力于跨学科复杂性研究的机构也是在这个时代成立的: 圣菲研究所是由美国洛斯阿拉莫斯国家实验室（Los Alamos National Laboratory）的科学家于1984年建立的，密歇根大学的 BACH 小组也是在20世纪80年代中期建立的。

使用'''元胞自动机 Cellular Automata'''，科学家们能够指定由元胞网格组成的系统，其中每个元胞只占据一些有限的状态，状态之间的变化完全由相邻元胞的状态控制。随着人工智能和微型计算机能力的进步，这些方法促进了“混沌理论”和“复杂性理论”的发展，这反过来又重新引起了人们对跨学科的复杂物理和社会系统的兴趣。明确致力于跨学科复杂性研究的机构也是在这个时代成立的: 圣菲研究所是由美国洛斯阿拉莫斯国家实验室（Los Alamos National Laboratory）的科学家于1984年建立的，密歇根大学的 BACH 小组也是在20世纪80年代中期建立的。

This cellular automata paradigm gave rise to a third wave of social simulation emphasizing agent-based modeling. Like micro-simulations, these models emphasized bottom-up designs but adopted four key assumptions that diverged from microsimulation: autonomy, interdependency, simple rules, and adaptive behavior. In 1981, mathematician and political scientist Robert Axelrod and evolutionary biologist W.D. Hamilton published a major paper in Science titled "The Evolution of Cooperation" which used an agent-based modeling approach to demonstrate how social cooperation based upon reciprocity can be established and stabilized in a prisoner's dilemma game when agents followed simple rules of self-interest. Axelrod and Hamilton demonstrated that individual agents following a simple rule set of (1) cooperate on the first turn and (2) thereafter replicate the partner's previous action were able to develop "norms" of cooperation and sanctioning in the absence of canonical sociological constructs such as demographics, values, religion, and culture as preconditions or mediators of cooperation. Throughout the 1990s, scholars like William Sims Bainbridge, Kathleen Carley, Michael Macy,  and John Skvoretz developed multi-agent-based models of generalized reciprocity, prejudice, social influence, and organizational information processing. In 1999, Nigel Gilbert published the first textbook on Social Simulation: Simulation for the social scientist and established its most relevant journal: the Journal of Artificial Societies and Social Simulation.

This cellular automata paradigm gave rise to a third wave of social simulation emphasizing agent-based modeling. Like micro-simulations, these models emphasized bottom-up designs but adopted four key assumptions that diverged from microsimulation: autonomy, interdependency, simple rules, and adaptive behavior. In 1981, mathematician and political scientist Robert Axelrod and evolutionary biologist W.D. Hamilton published a major paper in Science titled "The Evolution of Cooperation" which used an agent-based modeling approach to demonstrate how social cooperation based upon reciprocity can be established and stabilized in a prisoner's dilemma game when agents followed simple rules of self-interest. Axelrod and Hamilton demonstrated that individual agents following a simple rule set of (1) cooperate on the first turn and (2) thereafter replicate the partner's previous action were able to develop "norms" of cooperation and sanctioning in the absence of canonical sociological constructs such as demographics, values, religion, and culture as preconditions or mediators of cooperation. Throughout the 1990s, scholars like William Sims Bainbridge, Kathleen Carley, Michael Macy,  and John Skvoretz developed multi-agent-based models of generalized reciprocity, prejudice, social influence, and organizational information processing. In 1999, Nigel Gilbert published the first textbook on Social Simulation: Simulation for the social scientist and established its most relevant journal: the Journal of Artificial Societies and Social Simulation.

元胞自动机范式引发了强调'''基于主体建模 Agent-based Modeling'''的第三次社会模拟浪潮。与微观模拟一样，这些模型强调自下而上的设计，但采用了与微观模拟不同的四个关键假设: '''自主性 Autonomy'''、'''相互依赖性 Interdependency'''、'''简单规则 Simple Rules'''和'''适应性行为 Adaptive Behavior'''。1981年，数学家、政治学家阿克塞尔罗德（Robert Axelrod）和进化生物学家汉密尔顿（W.D. Hamilton）在《科学》杂志上发表了一篇名为《合作的进化》（The Evolution of Cooperation）的重要论文，该论文采用基于主体建模方法，论证了在一个囚徒困境博弈中，当主体遵循简单的自利规则时，互惠的社会合作是如何建立和稳定的。阿克塞尔罗德和汉密尔顿证明，主体遵循这样一套简单的规则: (1)在第一轮进行合作，(2)在其后重复伙伴以前的行动，能够在没有人口学差异、价值观、宗教和文化等社会规范作为合作的先决条件或中介的情况下制定合作和制裁的“规范”。整个20世纪90年代，像威廉·希姆斯·本布里奇（William Sims Bainbridge），Kathleen Carley，Michael Macy 和 John Skvoretz 这样的学者开发了基于多主体的广义互惠、偏见、社会影响和组织信息处理模型。1999年，吉尔伯特（Nigel Gilbert）出版了第一本关于社会模拟: 写给社会科学家的仿真模拟（Simulation for the social scientist）的教科书，并建立了它最相关的杂志: 人工社会和社会模拟杂志（the Journal of Artificial Societies and Social Simulation）。

元胞自动机范式引发了强调'''基于主体建模 Agent-based Modeling'''的第三次社会模拟浪潮。与微观模拟一样，这些模型强调自下而上的设计，但采用了与微观模拟不同的四个关键假设: '''自主性 Autonomy'''、'''相互依赖性 Interdependency'''、'''简单规则 Simple Rules'''和'''适应性行为 Adaptive Behavior'''。1981年，数学家、政治学家阿克塞尔罗德（Robert Axelrod）和进化生物学家汉密尔顿（W.D. Hamilton）在《科学》杂志上发表了一篇名为《合作的进化》（The Evolution of Cooperation）的重要论文，该论文采用基于主体建模方法，论证了在一个囚徒困境中，当主体遵循简单的自利规则时，互惠的社会合作是如何建立和稳定的。阿克塞尔罗德和汉密尔顿证明，主体遵循这样一套简单的规则: (1)在第一轮进行合作，(2)在其后重复伙伴以前的行动，能够在没有人口学差异、价值观、宗教和文化等社会规范作为合作的先决条件或中介的情况下制定合作和制裁的“规范”。整个20世纪90年代，像威廉·希姆斯·本布里奇（William Sims Bainbridge），Kathleen Carley，Michael Macy 和 John Skvoretz 这样的学者开发了基于多主体的广义互惠、偏见、社会影响和组织信息处理模型。1999年，吉尔伯特（Nigel Gilbert）出版了第一本关于社会模拟: 写给社会科学家的仿真模拟（Simulation for the social scientist）的教科书，并建立了它最相关的杂志: 人工社会和社会模拟杂志（the Journal of Artificial Societies and Social Simulation）。

===Data mining and social network analysis 数据挖掘和社会网络分析===

===Data mining and social network analysis 数据挖掘和社会网络分析===

turning textual data into network data.  The resulting networks, which can contain thousands of nodes, are then analysed by using tools from Network theory to identify the key actors, the key communities or parties, and general properties such as robustness or structural stability of the overall network, or centrality of certain nodes. This automates the approach introduced by quantitative narrative analysis, whereby subject-verb-object triplets are identified with pairs of actors linked by an action, or pairs formed by actor-object.

turning textual data into network data.  The resulting networks, which can contain thousands of nodes, are then analysed by using tools from Network theory to identify the key actors, the key communities or parties, and general properties such as robustness or structural stability of the overall network, or centrality of certain nodes. This automates the approach introduced by quantitative narrative analysis, whereby subject-verb-object triplets are identified with pairs of actors linked by an action, or pairs formed by actor-object.

将文本数据转换为网络数据（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） 和前面一段是连起来的吗？）。由此产生的网络可以包含数千个'''节点 Nodes'''，然后利用网络理论中的工具对其进行分析，以确定关键参与者、关键群体，以及网络的总体特性如稳健性、结构稳定性，或某些节点的'''中心性 Centrality'''等。这使'''定量叙事分析Quantitative Narrative Analysis'''引入的方法得以自动化，据此，主语-动词-宾语三元组被看作由动作连接的成对行为者，或者由行为者-宾语形成的成对行为者。

将文本数据转换为网络数据（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） 和前面一段是连起来的吗？）。

 

由此产生的网络可以包含数千个'''节点 Nodes'''，然后利用网络理论中的工具对其进行分析，以确定关键参与者、关键群体，以及网络的总体特性如稳健性、结构稳定性，或某些节点的'''中心性 Centrality'''等。这使'''定量叙事分析Quantitative Narrative Analysis'''引入的方法得以自动化，据此，主语-动词-宾语三元组被看作由动作连接的成对行为者，或者由行为者-宾语形成的成对行为者。

===Computational content analysis 计算机内容分析 （名词翻译可吗？）===

===Computational content analysis 计算机内容分析 （名词翻译可吗？）===

计算社会学和其他研究领域一样面临着一系列的挑战。必须有意义地处理这些挑战（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） meaningfully怎么翻译才比较通顺？），才能对社会产生最大的影响。

计算社会学和其他研究领域一样面临着一系列的挑战。必须有意义地处理这些挑战（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） meaningfully怎么翻译才比较通顺？），才能对社会产生最大的影响。

 

正如前面所讨论的，社会分为不同层次。在其中的一个层次：个体层次中，'''微观-宏观联系 Micro-macro Link'''指的是创造更高层次的相互作用。关于微观-宏观链接有一系列问题等待回答。它们是如何形成的？它们什么时候汇聚？什么反馈被推到了较低的层次，他们是如何被推动的？（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） 语句不通顺啊，什么叫推到了较低层次的反馈。。。不懂不懂）

正如前面所讨论的，社会分为不同层次。在其中的一个层次：个体层次中，'''微观-宏观联系 Micro-macro Link'''指的是创造更高层次的相互作用。关于微观-宏观链接有一系列问题等待回答。它们是如何形成的？它们什么时候汇聚？什么反馈被推到了较低的层次，他们是如何被推动的？（--[[用户:嘉树|嘉树]]（[[用户讨论:嘉树|讨论]]） 语句不通顺啊，什么叫推到了较低层次的反馈。。。不懂不懂）

 

Another major challenge in this category concerns the validity of information and their sources. In recent years there has been a boom in information gathering and processing. However, little attention was paid to the spread of false information between the societies. Tracing back the sources and finding ownership of such information is difficult.

Another major challenge in this category concerns the validity of information and their sources. In recent years there has been a boom in information gathering and processing. However, little attention was paid to the spread of false information between the societies. Tracing back the sources and finding ownership of such information is difficult.