It's an exceedingly simple example used to illustrate the technique. The methods included in the python library are robust enough to work just as well on much larger and more complicated data-sets but that would be too difficult to follow for someone who isn't familiar with the subject.
I think it's hard to understand what the point is without a result that differs from the naive solution. That is, my naive "who's an important terrorist" is "who belongs to the most terrorist groups".
While belonging to the most terrorist groups will usually give the highest score, it's not quite the same as what betweenness actually measures - belonging to the most terrorist groups that are each large but do not share many members.
Comments
It's an exceedingly simple example used to illustrate the technique. The methods included in the python library are robust enough to work just as well on much larger and more complicated data-sets but that would be too difficult to follow for someone who isn't familiar with the subject.
I think it's hard to understand what the point is without a result that differs from the naive solution. That is, my naive "who's an important terrorist" is "who belongs to the most terrorist groups".
While belonging to the most terrorist groups will usually give the highest score, it's not quite the same as what betweenness actually measures - belonging to the most terrorist groups that are each large but do not share many members.