COURSES
INTRODUCTION TO NETWORK ANALYSIS
General Information
Aim:
This course is predominantly an applied statistical course. It aims to provide the basic theoretical and operational concepts to the student about Exploratory Social Network Analysis applied to demographic studies. The course will cover construction and use of relational data for network analysis applied to different research areas: publication networks, migration networks, cognitive networks and spatially explicit social representations. The empirical part of the course will be based on two main softwares: R and Gephi. I expect that students read the suggested literature specific to each method, as well participate in the data laboratory classes. At the end of the course I expect students to be able to manipulate data in all programs used during the course and apply the methods to specific areas of interest in Demography, Geography, Sociology, Economics, and Health Studies. Despite the exploratory emphasis of this course, a final talk on Inference for Social Networks will overview state of art models and inferential and computational limitations.
Tests and Grading:
- Assignment 1: parameters estimation and interpretation of a network (40 points) [Download]
- Assignment 2: network visualization and interpretation (30 points)
- Applied study: empirical application of network analysis to the student’s research area of interest (40 points)
More details:
Download the complete syllabus here. Download
Data
Scripts
Beamers
Class01_Part01_Beamer. Download
Class01_Part02_Beamer. Download
Class01_Part03_Beamer. Download
Class01_Part04_Beamer. Download
Class01_Part05_Beamer. Download
Class01_Part06_Beamer. Download
Class03_RMarkDown. Download
Class04_RMarkDown. Download
Class05_Beamer. Download
Class06_Beamer. Download
Class07_Beamer. Download
Class08_Beamer. Download
Video Classes
Extra Materials
References
Kolaczyk, Eric D. (2009). Statistical Analysis of Network Data: Methods and Models. Springer, New York.
Kolaczyk, Eric D. and Csárdi, Gábor. (2014). Statistical Analysis of Network Data with R. Springer, New York.
Luke, Douglas A. (2015). A User’s Guide to Network Analysis in R. Springer, New York.
Pereira WHS, Guedes GR, Duarte D, Ribeiro R, Amorim MA. (2017). Social Representations and Cognitive Networks: a Graph-based approach. MGEST. download