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Introduction to Network Analysis with R
Workshop Details
Date: November 26-27, 2020 (2-day worksop)
Time: 11 a.m. (Germany local time)
Venue: Online via Zoom
Workshop Language: English
Instructors: Dr. Markus Gamper, Dr. Raphael H. Heiberger
Schedule
26.11.2020, Thursday | |
11:00 – 12:30 | Presentation, introduction to the topic, objectives |
12:30 – 13:30 | Break (Lunch) |
13:30 – 15:00 | Theories/Definition |
15:00 – 15:15 | Break |
15:15 – 16:45 | Network data collection – Theory and practical exercises |
16:45 – 17:00 | Break |
17:00-18:30 | Important network measures |
27.11.2020, Friday | |
09:00 – 10:30 | Introduction to R – Analysis of network data with R |
10:30 – 10:45 | 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 | Break |
15:15 – 16:45 | Analysis of network data with R (What are ERGMs) |
Workshop 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
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.