Statistical Analysis of Social Networks

Uitgebreide vaknaam	Statistical Analysis of Social Networks
Leerdoelen	Students develop problem awareness related to the analysis of interdependent data, in particular socio-centric network data. They gain knowledge about the prevalent statistical techniques to analyse these data, and develop the practical skills to perform these analyses with the pertinent software packages.
Omschrijving	Social network analysis is the study of interdependence, and as such at odds with the independence assumptions underlying most of the common statistical methods. Moreover, network researchers often are interested in understanding network-level properties as emergent consequence of individual relational behaviour. The analysis of social network data therefore requires tools that are designed to deal with network interdependence as well as emergence. In this course, the two most prominent approaches achieving this dual task stand central: exponential random graph models and stochastic actor-oriented models. On the one hand, these can be calibrated to empirical data sets. This makes it possible to assess empirical evidence for network mechanisms of interdependence, like reciprocation, clustering, homophily, or peer influence. On the other hand, they can be used for generating artificial data, which makes it possible to systematically study emergent phenomena like segregation or hierarchy formation. In the accompanying computer labs and assignments, students will learn how to practically work with these models, making use of different R-based software packages.
Uren per week	2
Onderwijsvorm	computerpracticum, hoorcollege (attendance of the computer practicals is mandatory)
Toetsvorm	opdrachten
Vaksoort	master
Coördinator	dr. C.E.G. Steglich
Docent(en)	dr. C.E.G. Steglich
Verplichte literatuur	Titel Auteur ISBN Prijs A Users's Guide to Network Analysis in R Douglas A. Luke 978-3-319-23883-8 ca. €  50,00 The literature will be augmented by published articles linked to via Nestor.
Entreevoorwaarden	Participants should have a basic understanding of statistical principles (bachelor level statistics) and data analysis in the R statistical software environment. Prior knowledge of social networks is of advantage, but not required.
Opmerkingen	You can acquire the book as an e-book. We will not cover everything in it, just the data-handling and statistical inference aspects.
Opgenomen in	Opleiding Jaar Periode Type Research Master, Behavioural and Social Sciences (ReMa)  (ReMa) 1 semester I a keuze