1.
Proc Conf Assoc Comput Linguist Meet
; 2016: 1044-1053, 2016 Aug.
Article
in English
| MEDLINE
| ID: mdl-27795613
ABSTRACT
We construct a humans-in-the-loop supervised learning framework that integrates crowdsourcing feedback and local knowledge to detect job-related tweets from individual and business accounts. Using data-driven ethnography, we examine discourse about work by fusing language-based analysis with temporal, geospational, and labor statistics information.