Tag: Introduction to Social Networks
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ISN: Communities and cliques
Dyads are not yet interesting for network research. However, starting at triads interesting behaviour appear. In triads, balance and control appear. Triads appear more commonly in social networks than in random graphs. Clustering coeffcient The clustering coefficient measures the amount of transitivity in a network. When A is related to B, and B is in…
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ISN: Data Collection Strategies
Data collection refers to the collection of an offline social network. The information about a particular community is collect. A group needs to be defined (boundaries), which may be easy (e.g. school class or company) or difficult (e.g. needle-sharing). Complete network data A group with clear boundaries, such as a formal group or organisation. All…
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ISN: Positions in Social Networks
Positions in a network are important for different reasons such as well-being. In the following several concepts will be introduced to gauge positions in a social networks. Structural balance People prefer balanced relationship structures. According to Heider (Heider, 1946), imbalances cause psychological distress. To balance people create or drop ties. However, balance may not be…
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ISN: Network visualisation
Today’s topic will be to visualise networks and centrality measures. We visualise a network to better understand the underlying data. A visualisation should be driven by the question that we would like to answer. Nonetheless, visualisations are by their nature exploratory. Also, visualisations do not provide evidence for hypothesis. Visualisation usually tries to convey information…
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ISN: What are Social Networks?
Social networks are based on relations between two or a few individuals from friendships over contracts to work contacts. Throughout the course, the theory behind social networks will be put into context with methods of comparing and applying social networks. Examples from different scientific disciplines will be used to illustrate the social networks. Network descriptives…