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Shedding New Light on the Language of the Dark Web. (arXiv:2204.06885v1 [cs.CL])
April 15, 2022, 1:11 a.m. | Youngjin Jin, Eugene Jang, Yongjae Lee, Seungwon Shin, Jin-Woo Chung
cs.LG updates on arXiv.org arxiv.org
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 …
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