[Coursera]Social and Economic Networks: Models and Analysis课程1月6号开课

这个课是The Open-Source Data Science Masters - Curriculum（http://datasciencemasters.org/）中Analysis部分推荐的课程， 这个Curriculum list之前小K姐也有发帖推荐过（http://www.1point3acres.com/bbs/thread-71418-1-1.html）。

课程链接：https://www.coursera.org/course/networksonline

About the Course
Social networks pervade our social and economic lives.   They play a central role in the transmission of information about job opportunities and are critical to the trade of many goods and services. They are important in determining which products we buy, which languages we speak, how we vote, as well as whether or not we decide to become criminals, how much education we obtain, and our likelihood of succeeding professionally.   The countless ways in which network structures affect our well-being make it critical to understand how social network structures impact behavior, which network structures are likely to emerge in a society, and why we organize ourselves as we do.  This course provides an overview and synthesis of research on social and economic networks, drawing on studies by sociologists, economists, computer scientists, physicists, and mathematicians.

Course Format
The course will run for seven weeks, plus two for the final exam.  Each week there will be video lectures available, as well as a standalone problem set and some occasional data exercises, and there will be a final exam at the end of the course for those who wish to earn a course certificate.  


Course Syllabus
Week 1: Introduction, Empirical Background and Definitions
Examples of Social Networks and their Impact, Definitions, Measures and Properties: Degrees, Diameters, Small Worlds, Weak and Strong Ties, Degree Distributions
http://www.1point3acres.com/bbs/thread-80404-1-1.html 进度贴 && 讨论帖

Week 2: Background, Definitions, and Measures Continued
Homophily, Dynamics,  Centrality Measures: Degree, Betweenness, Closeness, Eigenvector, and Katz-Bonacich. Erdos and Renyi Random Networks: Thresholds and Phase Transitions,
http://www.1point3acres.com/bbs/thread-80960-1-1.html进度贴 && 讨论帖
Week 3: Random Networks
Poisson Random Networks, Exponential Random Graph Models,  Growing Random Networks, Preferential Attachment and Power Laws, Hybrid models of Network Formationhttp://www.1point3acres.com/bbs/thread-81638-1-1.html进度贴 && 讨论帖

Week 4:   Strategic Network Formation
Game Theoretic Modeling of Network Formation, The Connections Model, The Conflict between Incentives and Efficiency, Dynamics, Directed Networks, Hybrid Models of Choice and Chance
http://www.1point3acres.com/bbs/thread-82120-1-1.html进度贴 && 讨论帖

Week 5:  Diffusion on Networks.
Empirical Background, The Bass Model, Random Network Models of Contagion, The SIS model, Fitting a Simulated Model to Data
http://www.1point3acres.com/bbs/thread-83008-1-1.html进度贴 && 讨论帖

Week 6:  Learning on Networks.
Bayesian Learning on Networks, The DeGroot Model of Learning on a Network, Convergence of Beliefs, The Wisdom of Crowds, How Influence depends on Network Position.
http://www.1point3acres.com/bbs/thread-84065-1-1.html进度贴 && 讨论帖

Week 7: Games on Networks.
Network Games, Peer Influences:  Strategic Complements and Substitutes, the Relation between Network Structure and Behavior, A Linear Quadratic Game, Repeated Interactions and Network Structures.
http://www.1point3acres.com/bbs/thread-84303-1-1.html进度贴 && 讨论帖

Recommended Background
The course has some basic prerequisites in mathematics and statistics.  For example, it will be assumed that students are comfortable with basic concepts from linear algebra (e.g., matrix multiplication), probability theory (e.g., probability distributions, expected values, Bayes' rule), and statistics (e.g., hypothesis testing), and some light calculus (e.g., differentiation and integration).  Beyond those concepts, the course will be self-contained.

有兴趣跟课的同学可以在下面留言，有问题大家一起讨论。

来围观一下~

和几个教授聊了之后才发现 图模型 现在好热啊~~
我认识的教授之前做随机过程的、做微分方程的现在都开始做复杂网络了。。

这门课算是复杂网络的科普了吧，果断支持！

EroicaCMCS 发表于 2014-1-3 08:59
和几个教授聊了之后才发现 图模型 现在好热啊~~
我认识的教授之前做随机过程的、做微分方程的现在都开始做 ...

是呀是呀，而且很多不同的领域都在做network。 那些图看上去都好酷的样子，趁这门课的机会了解一下。

这个跟graphical model是一回事不？

打算注册一个试试 看看能否跟下来

小K 发表于 2014-1-6 09:51
这个跟graphical model是一回事不？

这个还想问你的。。。
个人感觉有Probabilistic Graphical Models和这个有交集，比如Markov Networks和Random Networks(没研究过，看到名字大概是差不多的吧)，但不全一样

跟一个prof讨论过这个问题，感觉图模型就是个筐，什么背景的人都可以沾边，然后做的角度完全不同了，比如：动力系统 or 随机，还有控制论？(prof说的，不明觉历)

已经注册了  开始上课！

小K 发表于 2014-1-6 09:51
这个跟graphical model是一回事不？

个人觉得图论更抽象，研究的主要是数学模型
network现在更侧重于结合某一行业，比如social network，transportation network等，还有需要研究某一网络的性质，比如可靠性，就是新的领域，这个图论里没有

wesley 发表于 2014-1-8 05:03
个人觉得图论更抽象，研究的主要是数学模型
network现在更侧重于结合某一行业，比如social network，tra ...

嗯 确实有很多方向可以做
研究稳定性，微分方程\动力系统背景的人可以做
加了一点随机，可以研究极限分布神马的，概率\随机过程背景的人可以做
研究同步的，一些工程背景的人可以搞
还有一些基于实证的东西，文科出身的 传播学、经济学的都可以涉及
大概是这样吧。。。不懂随便说。。。。