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计算社会科学

Computational Social Science
课程网址: http://videolectures.net/kdd2010_jensen_css/  
主讲教师: David Jensen
开课单位: 麻省大学
开课时间: 2010-10-01
课程语种: 英语
中文简介:
知识发现和数据挖掘方面的研究和应用越来越多地解决社会科学中一些最基本的问题:是什么决定了社会网络的结构和行为?什么影响消费者和选民的偏好?社会系统的参与如何影响诸如欺诈、技术采用或资源分配等行为?这些问题通常是第一次通过分析大量的数据集来检验,这些数据集记录了个体在物理和虚拟世界中的行为和互动。 一种新的科学努力——计算社会科学——正出现在社会科学和计算机科学的交汇处。该领域从心理学、社会学、经济学和其他社会科学以及计算机科学的形式语言和算法中汲取了丰富的现有理论基础。其结果是一个前所未有的机会来革命社会科学,扩大计算机科学的范围和影响,并使决策者能够理解复杂的系统和社会互动,我们必须管理,以解决经济福利、能源生产、可持续性、医疗保健、教育和犯罪的基本挑战。 计算社会科学为KDD的研究人员和实践者提出了一系列令人印象深刻的新任务和技术挑战。这些包括建模具有时间、空间和关系依赖性的复杂系统;确定因果关系而不仅仅是联系;有反馈的建模系统;并以保护个人隐私的方式进行分析。这些挑战中有许多以令人惊讶和鼓舞的基本方式相互作用。它们共同指向了知识发现和数据挖掘令人兴奋的新未来。
课程简介: Research and applications in knowledge discovery and data mining increasingly address some of the most fundamental questions of social science: What determines the structure and behavior of social networks? What influences consumer and voter preferences? How does participation in social systems affect behaviors such as fraud, technology adoption, or resource allocation? Often for the first time, these questions are being examined by analyzing massive data sets that record the behavior and interactions of individuals in physical and virtual worlds. A new kind of scientific endeavor - computational social science - is emerging at the intersection of social science and computer science. The field draws from a rich base of existing theory from psychology, sociology, economics, and other social sciences, as well as from the formal languages and algorithms of computer science. The result is an unprecedented opportunity to revolutionize the social sciences, expand the reach and impact of computer science, and enable decision-makers to understand the complex systems and social interactions that we must manage in order to address fundamental challenges of economic welfare, energy production, sustainability, health care, education, and crime. Computational social science suggests an impressive array of new tasks and technical challenges to researchers and practitioners of KDD. These include modeling complex systems with temporal, spatial, and relational dependence; identifying cause and effect rather than mere association; modeling systems with feedback; and conducting analyses in ways that protect the privacy of individuals. Many of these challenges interact in fundamental ways that are both surprising and encouraging. Together, they point to an exciting new future for knowledge discovery and data mining.
关 键 词: 知识发现; 数据挖掘; 社会系统; 计算社会科学
课程来源: 视频讲座网
数据采集: 2022-11-23:chenjy
最后编审: 2022-11-23:chenjy
阅读次数: 36