TWeet NLP (Carnegie Mellon)
From the webpage:
We provide a tokenizer, a part-of-speech tagger, hierarchical word clusters, and a dependency parser for tweets, along with annotated corpora and web-based annotation tools.
See the website for further details.
I can understand vendors mining tweets and try to react to every twitch in some social stream but the U.S. military is interested as well.
“Customer targeting” in their case has a whole different meaning.
Assuming you can identify one or more classes of tweets, would it be possible to mimic those patterns, albeit with some deviation in the content of the tweets? That is what tweet content is weighted heavier that other tweet content?
I first saw this in a tweet by Peter Skomoroch.