Introduction to Network Analysis with R (Online Workshop!)
Lecturer(s):
Dr. Markus Gamper, Dr. Raphael H. Heiberger
Date: 15.02 - 16.02.2021
ics-fileLocation: Online via Zoom / Course language: English
About the lecturer - Dr. Markus Gamper
About the lecturer - Dr. Markus Gamper
PD Dr. Markus Gamper is Assistant Professor at the Faculty of Humanities at the University of Cologne in Germany. He received his PhD from the University of Trier (Germany) and was visiting professor at the University of Autonomous University of Aguascalientes (Mexico). For many years, he has been an co-organizer and lecturer at the Trierer Summer School on social networks and co-inventor of the network software VennMaker. His research interests include social networks (qualitative and quantitative), social inequalities, sociology of religion and migration.
About the lecturer - Dr. Raphael H. Heiberger
About the lecturer - Dr. Raphael H. Heiberger
Dr. Raphael H. Heiberger is Tenure-Track Professor at the Institute for Social Sciences of the University of Stuttgart. He is head of the newly founded department on Computational Social Science. He received his PhD from the University of Bamberg (Germany) and was visiting scholar at UCLA and a Fulbright-Fellow at UC Berkeley. He is a permanent member of the McFarland Lab at Stanford University. For several years, he enjoyed being a lecturer at the Trierer Summer School on social networks. Besides various aspects of Social Network Analysis (dynamics, statistical modelling, theory), his research interests focus on Natural Language Processing, Bayesian Statistics (esp. Machine Learning) and, more generally, the application of computational methods on social phenomena like markets, media discourse or inequality.
Course description
This workshop provides an introduction into theoretical concepts as well as methods of data collection and analysis for social networks with R. The first day is dedicated to definitions and terminologies, influential models and their importance for the empirical collection of network data. We investigate several examples of research (data) and reflect on suitable research questions and requirements of research designs in the process of collecting data. Various approaches are discussed, along with the potential drawbacks and biases of the resulting measures. We also provide examples for network questions from traditional survey questionnaires. In addition, we will analyze social networks with the open-source software R. We start with introducing two of the most popular packages for SNA in R, “igraph” and “statnet”. After understanding relevant objects and packages' organization, we describe the intuition behind structural and positional network metrics, such as density, centrality, or modularity, and practice their calculation as well as their visualization.
Keywords
quantitative methods,
research design,
data collection and analysis,
complete networks,
R,
Data Analysis,
Computational Social Sciences,
R,
Workshops,
1-3 Days,
Online,
Beginner Learning objectives
After completion of this workshop, participants should be able to 1) cite and critically reflect the relevant key literature on social networks, 2) develop a research design aimed at collecting quantitative complete network data with the help of name generators, and 3) analyze positional and structural characteristics of networks using a R.
Prerequisites
Participants should possess a general affinity toward social science theory. Participants should also be open to acquainting themselves with quantitative methods. However, no advanced statistical knowledge is required.
Schedule
Schedule
Monday, 15.02. |
10:00 - 11:15 | Presentation, introduction tot he topic, objectives |
11:15-11:30 | Coffee-Break |
11:30 - 12:00 | Theories/Definition |
12:30 - 13:30 | Break (Lunch) |
13:30-15:00 | Theories/Network data collection |
15:00-15:15 | Coffee-Break |
15:15-16:45 | Important network measures |
16:45-17:00 | Break |
17:00-18:30 | Important network measures |
Tuesday, 16.02., |
09:00 - 10:30 | Introduction to R - Analysis of network data with R |
10:30 - 10:45 | Coffee-Break |
10:45 - 12:15 | Analysis of network data with R |
12:15 - 13:30 | Break (Lunch) |
13:30 - 15:00 | Analysis of network data with R |
15:00 - 15:15 | Coffee-Break |
15:15 - 16:45 | Analysis of network dara with R (What are ERGMs) |
More Information
More Information
Participation fee
Academic/non-profit rate | 240 EUR |
Commercial rate | 480 EUR |
Student rate* | 160 EUR |
*Admission required