Abstract
Complaining is a basic speech act regularly
used in human and computer mediated communication to express a negative mismatch between reality and expectations in a particular situation. Automatically identifying complaints in social media is of utmost importance for organizations or brands to improve
the customer experience or in developing dialogue systems for handling and responding to
complaints. In this paper, we introduce the first
systematic analysis of complaints in computational linguistics. We collect a new annotated
data set of written complaints expressed in English on Twitter.1 We present an extensive linguistic analysis of complaining as a speech act
in social media and train strong feature-based
and neural models of complaints across nine
domains achieving a predictive performance of
up to 79 F1 using distant supervision