Ok, so here’s a question:
Could you prove that different people and/or governments define “terrorist” differently? And that what gets defined as a terrorist dictates the groups and individuals that are targeted? I wouldn’t be surprised if there was high variability in the characteristics that add up to a “terrorist” between different countries. I also wouldn’t be surprised if the definition targets groups and individuals that threaten the government more so than it targets groups and individuals that threaten the people. This is a possible study, right?
Next:
It is an easy analogy between a person’s moods and a place’s weather. Perhaps this is so because the processes that underlie both of them share important features. Consider: weather has broad patterns that can be identified but are hard to predict specifically because they are influenced by very small fluctuations in the environment. Moods are similar, especially if it ends up that they are dictated by chaotic chemical changes in the brain. Unfortunately, the analogy falls apart when you try to figure out what a person’s environment translates to for weather patterns. My best guess would be the earth, since I’m not counting earthquakes as weather, 
but I don’t think that works very well.
Finally:
The current state of social network analysis focuses on a vertex / edge description. This makes sense for the data that has been dealt with most — web page links, citation networks, social network websites like Friendster or MySpace, etc. However, I think that real social network behavior is probably closer to chemical reactions, with important qualitative features of the vertices, the people, and the edges, their interactions. It’s like the field is trying to do chemistry with a single element at a time. Fil’s work is at least a step in the right direction, because (using the vertex / edge description and web pages) it adds the content of the web pages as a predictor for a link being made from one page to the other.
