Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Shedding New Light on the Language of the Dark Web   The hidden nature and the limited accessibility of the Dark Web, combined
with the lack of public datasets in this domain, make it difficult to study its
inherent characteristics such as linguistic properties. Previous works on text
classification of Dark Web domain have suggested that the use of deep neural
models may be ineffective, potentially due to the linguistic differences
between the Dark and Surface Webs. However, not much work has been done to
uncover the linguistic characteristics of the Dark Web. This paper introduces
CoDA, a publicly available Dark Web dataset consisting of 10000 web documents
tailored towards text-based Dark Web analysis. By leveraging CoDA, we conduct a
thorough linguistic analysis of the Dark Web and examine the textual
differences between the Dark Web and the Surface Web. We also assess the
performance of various methods of Dark Web page classification. Finally, we
compare CoDA with an existing public Dark Web dataset and evaluate their
suitability for various use cases.

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The categories of this paper are: q-fin
11
The categories of this paper are: hep-lat
26
The categories of this paper are: bayes-an
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The categories of this paper are: comp-gas
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The categories of this paper are: dg-ga
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The categories of this paper are: acc-phys
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The categories of this paper are: patt-sol
6
The categories of this paper are: astro-ph
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The categories of this paper are: plasm-ph
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The categories of this paper are: hep-ex
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The categories of this paper are: cmp-lg
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The categories of this paper are: nucl-ex
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The categories of this paper are: quant-ph
3
The categories of this paper are: physics
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The categories of this paper are: adap-org
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The categories of this paper are: hep-th