Scientific Coordination
Dr.
Marlene Mauk
Tel: +49 221 47694-579
Marlene Mauk
Tel: +49 221 47694-579
Administrative Coordination
Noemi Hartung
Tel: +49 621 1246-211
Tel: +49 621 1246-211
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Social Network Analysis with R
About
Location:
Mannheim B6, 4-5
Mannheim B6, 4-5
Course duration:
9:30-16:30 CEST
General Topics:
Course Level:
Format:
Software used:
Duration:
Language:
Fees:
Students: 500 €
Academics: 750 €
Commercial: 1500 €
Keywords
Additional links
Lecturer(s): Michal Bojanowski
Course description
The course will provide a hands-on tour through the important concepts and methods of Social Network Analysis (SNA). The main goal is to put the participants on a well-lit road towards conducting a typical social-network-analytic project comfortably on their own using R. The focus is on the practical application of key ideas of SNA rather than discussing (social) theories standing behind them. Nonetheless, pointers to the relevant theoretical and applied literature will be provided.
To this end the course will discuss importing network data from various formats, managing network data within R, basic SNA descriptives (including density, transitivity, homophily/segregation, and centrality), community detection, creating effective network visualizations. The course will conclude with coverage of the basics of statistical modeling of networks with Exponential-family Random Graph Models (ERGM) and Stochastic Actor-Oriented Models (SAOM).
Course meetings will consist of two parts. The first part will consist of a presentation, demonstration and discussions on various SNA concepts and methods. The second part will be focused on hands-on training in applying the presented concepts and tools using real data. While the instructors will provide datasets for these exercises, participants are encouraged to bring their own data.
For additional details on the course and a day-to-day schedule, please download the full-length syllabus.
Target group
Participants will find the course useful if:
Learning objectives
By the end of the course participants will:
Organisational structure of the Course
The course will be organized in two 3-hour sessions: lecture/presentation and hands-on lab. Presentations will introduce necessary concepts and demonstrate the discussed tools. Lab sessions will enable the participants to practice, with guidance from the instructors, applying SNA concepts and using tools on real network datasets.
Prerequisites
For those who would like a primer or refresher in R, we recommend taking the online workshop "Introduction to R" that takes place from 05-07 September 2023.
Software and hardware requirements
Participants are expected to bring their own laptops with the following software installed:
Agenda
Monday, 25.09. |
Tuesday, 26.09. |
Wednesday, 27.09. |
Thursday, 28.09. |
Friday, 29.09. |