Course teacher(s)
Matteo GAGLIOLO (Coordinator)ECTS credits
5
Language(s) of instruction
english
Course content
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Networks: definitions, terminology, matrix representation
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Network data in the social sciences
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R basics and network-related packages
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Graphical representation of network data
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Basic global and local measures
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Centrality measures
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Community structure
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Social capital and hierarchy
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Influence
Objectives (and/or specific learning outcomes)
Acquiring the fundamental theoretical background and practical skills to perform a quantitative analysis of network data.
Teaching methods and learning activities
The course will be held in a computer room, combining theory with its immediate application, mostly using the R language via the RStudio interface. Prior knowledge of R is not assumed. Additional free software may be used for visualisation.
Contribution to the teaching profile
Quantitative methods
References, bibliography, and recommended reading
TBA
Other information
Contacts
Matteo GAGLIOLO <Matteo.Gagliolo@ulb.ac.be>
Evaluation
Method(s) of evaluation
- Other
Other
Personal or group project consisting of an annotated analysis of a network dataset, to be presented and defended orally.
Language(s) of evaluation
- english
- french