Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Abuse is Contextual, What about NLP? The Role of Context in Abusive
  Language Annotation and Detection   The datasets most widely used for abusive language detection contain lists of
messages, usually tweets, that have been manually judged as abusive or not by
one or more annotators, with the annotation performed at message level. In this
paper, we investigate what happens when the hateful content of a message is
judged also based on the context, given that messages are often ambiguous and
need to be interpreted in the context of occurrence. We first re-annotate part
of a widely used dataset for abusive language detection in English in two
conditions, i.e. with and without context. Then, we compare the performance of
three classification algorithms obtained on these two types of dataset, arguing
that a context-aware classification is more challenging but also more similar
to a real application scenario.

19
The categories of this paper are: eess
18
The categories of this paper are: econ
14
The categories of this paper are: math-ph
10
The categories of this paper are: q-bio
4
The categories of this paper are: cond-mat
16
The categories of this paper are: stat
33
The categories of this paper are: plasm-ph
20
The categories of this paper are: acc-phys
32
The categories of this paper are: atom-ph
22
The categories of this paper are: chao-dyn
25
The categories of this paper are: patt-sol
35
The categories of this paper are: mtrl-th
21
The categories of this paper are: adap-org
29
The categories of this paper are: funct-an
3
The categories of this paper are: physics
7
The categories of this paper are: hep-th