Posts tagged ‘betweenness’
Why Anchorage is not (that) important: Binary ties and Sample selection
A surprising finding when analysing airport networks is the importance of Anchorage airport in Alaska. In fact, it is the most central airport in the network when applying betweenness! I do not believe this finding is completely accurate due to two reasons: (1) there is a potential for measurement error when not including tie weights (i.e., assigning the same importance to the connection between London Heathrow and New York’s JFK as to the connection between Pack Creek Airport and Sitka Harbor Sea Plane Base in Alaska), and (2) relying on US data only leads to sample selection as the airport network is a global system. This post highlights how to use a weighted betweenness measure as well as the extent of the sample selection issue.
Article: For the few not the many? The effects of affirmative action on presence, prominence, and social capital of women directors in Norway
A paper called “For the few not the many? The effects of affirmative action on presence, prominence, and social capital of women directors in Norway” that I have co-authored will be published in the Scandinavian Journal of Management. Governments have implemented various affirmative action policies to address vertical sex segregation in organizations. A gender representation law was introduced in Norway, which required public limited companies’ boards to have at least 40 percent representation of each sex by 2008. This law acted as an external shock, and this paper aims to explore its effects. In particular, it explores the gender bias, the emergence and sex of prominent directors, and directors’ social capital. We utilize data from May 2002 to August 2009 to analyze these aspects. The implied intention of the law was to create a larger pool of women acting as directors on boards, and the law has had the effect of increasing the representation of women on boards. However, it has also created a small elite of women directors who rank among the top on a number of proxies of influence.
Continue Reading September 30, 2010 at 4:02 pm Leave a comment
Article: Node centrality in weighted networks: Generalizing degree and shortest paths
A paper called “Node centrality in weighted networks: Generalizing degree and shortest paths” that I have co-authored will be published in Social Networks. Ties often have a strength naturally associated with them that differentiate them from each other. Tie strength has been operationalized as weights. A few network measures have been proposed for weighted networks, including three common measures of node centrality: degree, closeness, and betweenness. However, these generalizations have solely focused on tie weights, and not on the number of ties, which was the central component of the original measures. This paper proposes generalizations that combine both these aspects. We illustrate the benefits of this approach by applying one of them to Freeman’s EIES dataset.
Betweenness in weighted networks
This post highlights a generalisation of Freeman’s (1978) betweenness measure to weighted networks implicitly introduced by Brandes (2001) when he developed an algorithm for calculating betweenness faster. Betweenness is a measure of the extent to which a node funnels transactions among all the other nodes in the network. By funnelling the transactions, a node can broker. This could be by taking a cut (e.g. Ukraine controls most gas pipelines from Russia to Europe) or distorting the information being transmitted to its advantage.