課程資訊
課程名稱
網絡資料分析與模式
Network Data Analysis and Models 
開課學期
109-2 
授課對象
學程  人口學程  
授課教師
溫在弘 
課號
Geog5076 
課程識別碼
228 U2880 
班次
 
學分
3.0 
全/半年
半年 
必/選修
選修 
上課時間
星期五2,3,4(9:10~12:10) 
上課地點
地理一教室 
備註
本課程中文授課,使用英文教科書。[人口學程]選修領域(四)遷移與空間。
總人數上限:30人 
Ceiba 課程網頁
http://ceiba.ntu.edu.tw/1092_Geog5076 
課程簡介影片
 
核心能力關聯
本課程尚未建立核心能力關連
課程大綱
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課程概述

This course explores quantitatively the concepts and applications of network data analysis and how these theories assist scientists in understanding the complex patterns of connections and relationships that shape our lives. Students will acquire the ability to use the modeling and statistical methods to analyze link-node structures and behaviors of a complex network. They will also explore some emerging topics on human behavior analysis, social interactions and peer influence, disease transmission, innovation diffusion, and spatial structures of migration. 

課程目標
The objectives of the course are to guide students on how to describe and characterize quantitatively various types of network topology and the use of appropriate analytical methods and statistical models to explain the features of complex networks and mechanisms of the social-spatial process. 
課程要求
Course participation, weekly readings, and written assignments 
預期每週課後學習時數
 
Office Hours
 
參考書目
Borgatti, S. P., Everett, M. G., & Johnson, J. C. (2013). Analyzing Social
Networks. SAGE Publications. ISBN: 978-1446247419.
Newman (2010). Networks: An Introduction. New York: Oxford University Press
Menczer, Fortunato, Davis (2020), A First Course in Network Science, New York:
Cambridge University Press. ISBN: 978-1108471138. 
指定閱讀
Valente (2010). Social Networks and Health: Models, Methods, and Applications. New York: Oxford University Press.
Kolaczyk, Eric D., Csardi, Gabor (2020), Statistical Analysis of Network Data with R, New York: Springer-Verlag.
 
評量方式
(僅供參考)
 
No.
項目
百分比
說明
1. 
Mid term exam 
30% 
 
2. 
Final exam 
30% 
 
3. 
Weekly written assignments and discussion in class 
40% 
 
 
課程進度
週次
日期
單元主題
第1週
2/26  Course Introduction: Networks in Social and Geographical Spaces 
第2週
3/05  Networks as Social Relationships: An Introduction 
第3週
3/12  Network Data Collection and Visualization 
第4週
3/19  Measures for Ego-Networks: Structure Hole 
第5週
3/26  Network Measures: Centrality (Individual-level) 
第6週
4/02  * Spring break * 
第7週
4/09  Network Measures: Groups and Community Structures 
第8週
4/16  Network Measures: Positions and Structural Equivalence 
第9週
4/23  * Mid-term Exam * 
第10週
4/30  Lab: Creating R Shiny Dashboard 
第11週
5/07  Network-Level Measures + Two-mode Networks 
第12週
5/14  Network Autocorrelation Models 
第13週
5/21  Spatial Networks: Linking Geospatial Data 
第14週
5/28  Predicting with Networks: QAP Regression Models  
第15週
6/04  Exponential Random Graph Models (ERGM) 
第16週
6/11  Temporal Network Dynamics  
第17週
6/18  * Break * 
第18週
6/25  Final Report Submission