Sure. The problem is that the slang and abbreviation need to show up in their corpus. From what I understand, Google mostly uses Canadian and European Parliment proceedings for their sample. "LOL' dosn't show up much there...
One thing that they can do, is to use statistical models of language to infer what unknown words "should" mean. They could even incorporate phonetic priors (IE, "Qui" sounds like "ki").
Facebook right now has an oddly rich corpus of multi-lingual slang, they'd be in a good competitive position vs google-translate if they went through the effort to incorporate it into it's translation.
"In the period for which we have data, 1 in 7.9 whites stopped were arrested, compared with approximately 1 in 8.8 Hispanics and 1 in 9.5 blacks. These data are consistent with our general conclusion that the police are disproportionately stopping minorities; the stops of whites are more “efcient” and are more likely to lead to arrests"
Not really, no. It's about scale-free networks (Networks that have preferential attachment, IE, people with tons of friends are more likely to get new friends than people with no friends. Their degree distribution, IE, the number of friends, is power-law distributed as opposed to exponential distributions, which come from friendship being totally random). You can model social networks fairly well as scale-free networks empirically. Roughly speaking, the average distance between two random notes is proportional to the log of the log of the number of nodes.