課程資訊
課程名稱
社會與經濟網絡分析專題
Seminar on Social and Economic Networks 
開課學期
107-2 
授課對象
社會科學院  政治學系  
授課教師
李宣緯 
課號
PS5690 
課程識別碼
322 U2080 
班次
 
學分
2.0 
全/半年
半年 
必/選修
選修 
上課時間
星期四6,7(13:20~15:10) 
上課地點
社科研605 
備註
總人數上限:30人
外系人數限制:5人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1072PS5690_ 
課程簡介影片
 
核心能力關聯
核心能力與課程規劃關聯圖
課程大綱
為確保您我的權利,請尊重智慧財產權及不得非法影印
課程概述

(以中文授課)
Networks are ubiquitous in our modern society. A social network is a social structure made up of a set of social actors and other social interactions between actors. Social networks and the analysis of them is an inherently interdisciplinary academic field which emerged from sociology, political science, economics, psychology, computer science, applied mathematics, and statistics.

This course will provide the methods for the study of social and economic networks. We will explore both theoretical models and their applications to social, political and economic behavior. The course begins with an overview of basic backgrounds. We will then cover network properties, homophily, peer effects, social capital and trust, games on networks, information aggregation in networks, social learning, trade in networks, markets, voting, and other topics. One goal of the course is to identify potential research questions for students.

Students will work on their own final project. The final project involves preparing a detailed research report and an in-class presentation concerning either the analysis of a social or economic network or a theoretical contribution. Students will be working as a group of three. You can either work on the analysis of new social network datasets or extend existing papers idea. The presentation and report should focus on basic motivation, analysis, extensions, and future potential extension. Students need to schedule at least one meeting with the lecturer before their final presentation. The project will be due at the end of finals week and should be no longer than 10 pages.

Week 1: Overview of Network Analysis
Week 2: Introduction to Graph Theory; Describing and Measuring Networks
Week 3: Strong and Weak Ties
Week 4: Network Properties; Positive and Negative Relationships
Week 5: Random Networks; Exponential Random Graph Models
Week 6: Network Formation; Growing Random Networks
Week 7: Strategic Network Formation
Week 8: Modeling of Network Formation
Week 9: Review Session / Midterm Exam
Week 10: Decision, Behavior, and Games on Network
Week 11: Evolutionary Game Theory
Week 12: Diffusion on Networks
Week 13: Networks and Markets
Week 14: Markets and Information
Week 15: Voting on Networks
Week 16: Observing and Measuring Social Interaction
Week 17: Final Presentations 1
Week 18: Final Presentations 2
 

課程目標
The course provides an overview of models and techniques for analyzing social and economic networks. The course is meant for undergraduate and graduate students in College of Social Sciences with a good mastery of math/statistics who are interested both in the theoretical study of networks and in their application to political, social and economic phenomena.

By the end of this course, students will have: (1) Broad understanding of social network analysis. (2) Knowledge and tools to analyze social and economic networks. (3) The ability to understand research papers in the field of social networks. (4) The opportunity to work on a project that applies the techniques and ideas they learn during the semester.
 
課程要求
Quizzes 10%
Assignments 30%
Midterm 30%
Final Presentation and Report 30%

The final project involves preparing a detailed research report and an in-class presentation concerning either the analysis of a social or economic network or a theoretical contribution. Students will be working as a group of three. You can either work on the analysis of new social network datasets or extend existing papers idea. The presentation and report should focus on basic motivation, analysis, extensions, and future potential extension. Students need to schedule at least one meeting with the lecturer before their final presentation. The project will be due at the end of finals week
and should be no longer than 10 pages.

Networks are ubiquitous in our modern society. A social network is a social structure made up of a set of social actors and other social interactions between actors. Social networks and the analysis of them is an inherently interdisciplinary academic field which emerged from sociology, political science, economics, psychology, computer science, applied mathematics, and statistics.

This course will provide the methods for the study of social and economic networks. We will explore both theoretical models and their applications to social, political and economic behavior. The course begins with an overview of basic backgrounds. We will then cover network properties, homophily, peer effects, social capital and trust, games on networks, information aggregation in networks, social learning, trade in networks, markets, voting, and other topics. One goal of the course is to identify potential research questions for students.

By the end of this course, students will have: (1) Broad understanding of social network analysis. (2) Knowledge and tools to analyze social and economic networks. (3) The ability to understand research papers in the field of social networks. (4) The opportunity to work on a project that applies the techniques and ideas they learn during the semester.

The course provides an overview of models and techniques for analyzing social and economic networks. The course is meant for undergraduate and graduate students in College of Social Sciences with a good mastery of math/statistics who are interested both in the theoretical study of networks and in their application to political, social and economic phenomena.
 
預期每週課後學習時數
 
Office Hours
另約時間 備註: waynelee1217@gmail.com 
參考書目
待補 
指定閱讀
1. Matthew O. Jackson. Social and Economic Networks. Princeton University Press, 2008. (J)
2. David Easley and Jon Kleinberg. Networks, Crowds, and Markets: Reasoning about a Highly Connected World. Cambridge University Press, 2010. (EK)
Week 1 Reading assignment: J: Ch. 1; EK: Ch. 1
Week 2 Reading assignment: J: Ch. 2, 3; EK: Ch. 2
Week 3 Reading assignment: EK: Ch. 3
Week 4 Reading assignment: EK: Ch. 4, 5
Week 5 Reading assignment: J: Ch. 4
Week 6 Reading assignment: J: Ch. 5
Week 7 Reading assignment: J: Ch. 6
Week 8 Reading assignment: J: Ch. 11
Week 9 Midterm Exam
Week 10 Reading assignment: EK: Ch. 6; J: Ch. 9
Week 11 Reading assignment: EK: Ch. 7
Week 12 Reading assignment: J: Ch. 7; EK: Ch. 19
Week 13 Reading assignment: J: Ch. 10; EK: Ch. 10
Week 14 Reading assignment: EK: Ch. 22
Week 15 Reading assignment: EK: Ch. 23
Week 16 Reading assignment: J: Ch. 13
Week 17 Final Presentations
Week 18 Final Presentations
 
評量方式
(僅供參考)
   
課程進度
週次
日期
單元主題
第1週
2/21  課程簡介 
第3週
3/07  線性代數複習 
第4週
3/14  Overview of network science