Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: A Large-scale Dataset for Argument Quality Ranking: Construction and
  Analysis   Identifying the quality of free-text arguments has become an important task
in the rapidly expanding field of computational argumentation. In this work, we
explore the challenging task of argument quality ranking. To this end, we
created a corpus of 30,497 arguments carefully annotated for point-wise
quality, released as part of this work. To the best of our knowledge, this is
the largest dataset annotated for point-wise argument quality, larger by a
factor of five than previously released datasets. Moreover, we address the core
issue of inducing a labeled score from crowd annotations by performing a
comprehensive evaluation of different approaches to this problem. In addition,
we analyze the quality dimensions that characterize this dataset. Finally, we
present a neural method for argument quality ranking, which outperforms several
baselines on our own dataset, as well as previous methods published for another
dataset.

11
The categories of this paper are: hep-lat
22
The categories of this paper are: chao-dyn
12
The categories of this paper are: nucl-th
16
The categories of this paper are: stat
14
The categories of this paper are: math-ph
32
The categories of this paper are: atom-ph
27
The categories of this paper are: comp-gas
23
The categories of this paper are: solv-int
7
The categories of this paper are: hep-th
31
The categories of this paper are: ao-sci
21
The categories of this paper are: adap-org
5
The categories of this paper are: gr-qc
9
The categories of this paper are: nlin
18
The categories of this paper are: econ
6
The categories of this paper are: astro-ph
15
The categories of this paper are: nucl-ex