Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Automatically Identifying Complaints in Social Media   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.\footnote{Data
and code is available here:
\url{https://github.com/danielpreotiuc/complaints-social-media}} 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.

19
The categories of this paper are: eess
32
The categories of this paper are: atom-ph
4
The categories of this paper are: cond-mat
15
The categories of this paper are: nucl-ex
27
The categories of this paper are: comp-gas
31
The categories of this paper are: ao-sci
20
The categories of this paper are: acc-phys
8
The categories of this paper are: hep-ex
25
The categories of this paper are: patt-sol
29
The categories of this paper are: funct-an
22
The categories of this paper are: chao-dyn
33
The categories of this paper are: plasm-ph
18
The categories of this paper are: econ
36
The categories of this paper are: cmp-lg
11
The categories of this paper are: hep-lat
34
The categories of this paper are: chem-ph