The popular microblogging service Twitter (twitter.com) is one particularly fruitful source of user-created content, and a flurry of recent research has aimed to understand and exploit these data (Ritter et al., 2010;Sharifi et al., 2010;Barbosa and Feng, 2010;Asur and Huberman, 2010;O'Connor et al., 2010a;Thelwall et al., 2011).
the bulk of this work eschews the standard pipeline of tools which might enable a richer linguistic analysis; such tools are typically trained on newstext and have been shown to perform poorly on Twitter (Finin et al., 2010).