課程資訊
課程名稱
 社會網絡的經濟學分析
Economic Analysis of Social Networks 
開課學期
 108-2 
授課對象
 社會科學院  經濟學研究所  
授課教師
 謝志昇 
課號
 ECON7217 
課程識別碼
 323EM3760 
班次
  
學分
 3.0 
全/半年
 半年 
必/選修
 選修 
上課時間
 星期二2,3,4(9:10~12:10) 
上課地點
 社科401 
備註
 本課程以英語授課。
限碩士班以上
總人數上限：20人 
  
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
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課程概述

In this course, we will introduce economic analysis on social networks. Reflected by the rapid growing number of network studies in different economic fields, such as in labor, health, development, international, and financial economics, social (or economic) network has become an attractive and must-know subject for graduate students in economics, particularly in this big data era when network data become widely available.
We will begin this course by discussing the characterization of networks. Then we will visit some representative empirical studies which perform regressions based on network data. Next, we will discuss various kinds of statistical approaches for analyzing network data, including network sampling, community (cluster) detection, modelling network (spillover) effects, network formation, and relevant policy implications, etc.
Throughout this course, students do not only learn statistical models for networks, but also learn how to use the statistical software R to collect, arrange, and analyze network data. Students will also learn software such as Gephi to facilitate visualization of network graphs.

 

課程目標
 After completing this course, students should be:
1. Acquainted with basic terminologies in social and economic network analysis.
2. Familiar with theoretical development on network games
3. Able to perform econometric regressions on network data and provide economic interpretations.
4. Able to use software R to collect data and conduct network analysis.
 
課程要求
 待補 
預期每週課後學習時數
  
Office Hours
  
指定閱讀
 There is no required textbook 
參考書目
 1. Blume, L. E., Brock, W. A., Durlauf, S. N., & Ioannides, Y. M. (2011). Identification of social interactions. In Handbook of Social Economics (Vol. 1, pp. 853-964). North-Holland.
2. Borgatti, S. P., Everett, M. G., and Johnson, J. C. Analyzing Social Networks, Sage, 2013
3. Bramoulle, Yann, Andrea Galeotti, and Brian Rogers. The Oxford Handbook of the Economics of Networks. Oxford University Press, 2016.
4. De Paula (2017). Econometrics of Network Models, In B. Honore, A. Pakes, M. Piazzesi and L. Samuelson (Eds.), Advances in Economics and Econometrics: Theory and Applications: Eleventh World Congress (Econometric Society Monographs, pp.268-323), Cambridge: Cambridge University Press
5. Goldenberg, A., Zheng, A. X., Fienberg, S. E., & Airoldi, E. M. (2010). A survey of statistical network models. Foundations and Trends® in Machine Learning, 2(2), 129-233.
6. Hsieh, C.S., Lin, X., and Patacchini, E. (2019). Social Interaction Methods. To be appeared in Handbook of Labor, Human Resources and Population Economics.
7. Matthew, Jackson. Social and Economic Networks, Princeton University Press, 2008.
8. Matthew, Jackson and Zenou, Yves. Games on Networks, Handbook of Game Theory, Vol. 4, Amsterdam: Elsevier, 2014.
9. Kolaczyk, E. D., Statistical Analysis of Network Data: Method and Models, Springer, 2009.
10. Kolaczyk, E. D. and Csardi, G., Statistical Analysis of Network Data with R, Springer, 2014.
11. Newman, M. (2010) Networks: An Introduction, Oxford University Press
 
評量方式
(僅供參考)
  
No.
項目
百分比
說明
1. 
 course participation 
20% 
 There will be several on-lecture assignments which exercise the use of R 
2. 
 Course presentation  
40% 
 Students should present one article from the reference list 
3. 
 Research Proposal 
40% 
 Students have to hand in one research proposal at the end of the semester. Students should meet and discuss their proposals with the instructor at least once before submitting the proposal 
 
課程進度
週次
日期
單元主題
第1週
 3/03  Introduction and characterization of social networks  
第2週
 3/10  Regression with network data 
第3週
 3/17  Class cancellation  
第4週
 3/24  Network interactions  
第5週
 3/31  Network interactions (continued) 
第6週
 4/07  Static network formation  
第7週
 4/14  Static network formation (continued) 
第8週
 4/21  Student Presentation  
第9週
 4/28  Student Presentation  
第10週
 5/05  Dynamic network formation 
第11週
 5/12  Dynamic network formation (continued) 
第12週
 5/19  Network sampling 
第13週
 5/26  Network sampling (continued) 
第14週
 6/02  Community detection  
第15週
 6/09  Community detection (continued) 
第16週
 6/16  Student Presentation  
第17週
 6/23  Student Presentation